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FsF$F WF!8ssFF WfF0GFF WGF 0FFF 8X FF0F# FGF$FBEFF EFF#F!߀ F$F$FFJ!!2B!H FI!6!PM"' Mean : "71FF PMcF@PM") Standard Deviation : "72FF PMcF>PM"' Test Value : "7JFF PMcF 0'FFi#! F 6PM"$ One Tail Probability FBPM"' of more extreme value : " %FF 0McFF _H߀F F#1!2!J F $FFF14PRN:FF `.߀F 4 bstatprn.docFF$FFFb XFa b Fr,|d!ߪ!!߹F,|!ߪ!!߹F Tn!ߵ!PRINTF T!߷!OK F 8HFF:!3;!FF04!5!>FF5 aLH߀F!HF$F bD>߀F!F04!5!>F an>FD a445ݪ5߹F8HF 8b>FD b8445ݪ5߹F8HF$F$F$F bH߀F b^ F8HF4Printer not readyFFP$F$F aH F bH߀Fd8 F$F 8cF8 F8HF$FFF9!H!8!B!JFyFF2LY! "Student's T Distribution TestF LY! " Test ValueFFH!9ݤFVH!9߀FlH!9FlH!9߀FlH!9F(LY! "Degrees of FreedomFFH!9ݤF H!9ߠFfH!9FfH!9߀FfH!9F88F 89F f9FFF8HFXG8F e2! F8HF$F e FF fH߀F0J! F8B! F#J!B F e'F4incorrect dataFFFi 8eFnFF4CON:FF 4 FF#J!B F$FFF$F$FFJ!B F !FF8PM" "Student's T Probability TestFF PMcF"8߀B FT8w! FFPM" F PMcF>PM"' Test Value : "7JFF PMcF>PM"' Degrees of Freedom: "7BFF PMcF 0'FFi#! F 6PM"# One Tail ProbabilityFFBPM"' of more extreme value : " %FF 0McFF h,H߀F F#J!B F$FFFJH!8!1!!F FF.LY! "Poisson Distribution TestF(LY! "Expected FrequencyFFH!9ݨFtH!9߀FdH!9߀FdH!9߀FdH!9F(LY! "Low Frequency ValueFH!9ݨFqH!9ߠFeH!9FeH!9߀FeH!9F*LY! "High Frequency ValueFFH!9ݨFeH!9FuH!9FuH!9߀FuH!9F88F8HF 89FFF \FXG8F k! F8HF$F jFF kH߀9F01! F8! F8! F#1!! FF \F k'F4incorrect dataFFFi 8kFnFF4CON:FF#1!! Fa$FFF$FFF1 l> bstatprn.docF$O"M"F 8lF llT F$A"M"F 8lF$O"M"F$F$FF1!! FF!F!4PM" "Poisson Probability TestFF PMcF PMcF PMcF<PM"% Expected Occurrences : "71FF PMcF<PM"% Probability of from "7FF PMcF<PM" to "7" occurrences isF PMcF 0'FFi#! F 4PM" "" percentF 0McFF nH߀F F#1!! F $FFF19!H!8!J!!FFF(LY! "F Distribution TestFLY+! "F ValueFH!9FuH!9߀FFH!9߀FFH!9߀FFH!9F2LY! "Degrees of Freedom NumeratorFFH!9F H!9ߠFfH!9FfH!9߀FfH!9F4LY! "Degrees of Freedom DenominatorFFH!9F H!9FfH!9FfH!9߀FfH!9F88F 89FFF8HFXG8F qV! F8HF$F q0FF rPM"( Test Value : "7JF PMcF>PM"( Degrees of Freedom Numerator : "7F PMcF>PM"( Degrees of Freedom Denominator : "7F PMcF 0'FFi#! F 6PM"$ One Tail ProbabilityFBPM"( of more extreme value : " %F 0McFF t|H߀F F#J!! F $FFFJ9!H!8!5!!!F FF0LY! "Binomial Distribution TestFF,LY! "Probability of SuccessFFH!9FbH!9߀FlH!9ߠFlH!9߀FlH!9F&LY! "Number of TrialsFFH!9FoH!9ߠF H!9߀F H!9߀F H!9F,LY! "Low number of successesFH!9FbH!9FrH!9߀FrH!9߀FrH!9F.LY! "High number of successesFFH!9FmH!9FeH!9߀FeH!9߀FeH!9F88F 89F8HFFFXG8F x! F8HF$F wFF y*H߀9F05! F8! F8! F8! F \F#5!!! F \F x'F4incorrect dataFFFi 8yFnFF4CON:FF#5!!! F$FFF$FF5!!! FFF!F!2PM" "Binary Probability TestF PMcF PMcFPPM"% Probability of Success : "75" percentF PMcF<PM"% Number of Trials : "7FF PMcF8PM"" Probability of from "7F PMcF:PM" to "7" occurrences isFF PMcF 0'FFi#! F 6PM" "" percentFF 0McFF {jH߀F F#5!!! F$FFF59!H!8!B!JF FF2LY! "Chi Square Distribution TestFF LY! " Test ValueFFH!9ݤFVH!9߀FlH!9߀FlH!9߀FlH!9F(LY! 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F$FFFFFu v!F \F #A!E!!v F \FE 'ݠFF 4 improper data for testFF 88Fi4  Friedman TestF4CON:FFFF#v! F$FFFFFv v!F \F 0'#A!E!v F \FA 'ݠFF 4 improper data for testFF 8Fi 4 Kendal Concordance TestF4CON:FFFF#v!A߀ F$FFFFFv v!F \F0'#A!E!!w FF \FA ²'ݠFF 4 improper data for testFF 8Fi&4 Contingency Coefficient TestFF4CON:FFFF#w! F$FFFFFw v!F \F 0'#A!E!!v FF \FA Ø'ݠFF 4 improper data for testFF 8Fi4 Kruskal Wallis TestF4CON:FFFF#v! F$FFFFFvH!8!1FaDT!!(Kolmogorov Smirnov Test. Choose VariableF*!#н !н !!!!3!8 FFF x8F \F#A! F \F 'F4incorrect dataFFFi 8rFnFF4CON:FF24 Kolmogorov Smirnov Test on  Fo 0v'FF8Fr0'߀F#v! F$F$FFFFFv9!!H!8!1FoDT!!(1 SAMPLE VARIANCE TEST CHOOSE 1 VARIABLEFH!9F(H!9߈F H!9߀F H!9߀F H!9F88F*!#н !н !!!!3! F ,F,LY! "Test Standard deviationF 89FFF8HF  ! Ft8HF$F &H߀9F0x! F \F 0'#A! !x!y!B!2 F \FA Ǹ'F4incorrect dataFFFi 8FnFF4CON:FF64 Comparison of Variance Test on  F #y!B F$FFF$F$FFFFFyH!8!x!!FrDT!!)2 SAMPLE VARIANCE TEST CHOOSE 2 VARIABLESF*!#н !н !!!!3!8 FFF 8F \F&0'#A! ! !x!! F \FA P'F4incorrect dataFFFi 8FnFF4CON:FFJ4 Comparison of Variance Test on   and  F#x!! F $FFF$FFFxB!H!8!xF@T!!%WILCOXON RANK TEST CHOOSE 2 VARIABLESF*!#н !н !!!!3!8 FFF x8F \F 0'#A! ! !x F \FA 'ݠF4incorrect dataFFFi 8rFnFF4CON:FFH4 Wilcoxon Signed Ranks Test on   and  F 8BFn#x!B F$F$FFFFFxB!H!8!xF>T!!"KENDAL TAU TEST CHOOSE 2 VARIABLESF*!#н !н !!!!3!8 FFF 8F \F 0' #A! ! !x F \FA ̖'ݠF4incorrect dataFFFi 8FnFF4CON:FF>4 Kendal Tau Test on   and  F8BFT#x!B F$F$FFFFFxB!H!x!!FoBT!!&MANN WHITNEY U TEST CHOOSE 2 VARIABLESF*!#н !н !!!!3!B FFF BF \F&0'#A! ! !x!! 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""Standard Deviation of DistributionFFH!9FdH!9ߠFDH!9߀FDH!9߀FDH!9F88F 89F8HFFFXG8F z! F8HF$F TFF غH߀9F01! F02! F \F0x #A! !1!2 F \FA 8xݠF24incorrect dataFFFi 8خFn0'߀FFF44 Kolmogorov Normality Test on  FF4CON:FF#x! F$FFF$F$FFFxB!H!xF :T!!MEDIAN TEST CHOOSE 2 VARIABLESFO*!#н !н !!!!3!B FFF HBF \F 0' #A! ! !x F \FA 'ݠF4incorrect dataFFFi 8FF #I FH!9F$F H !9ߠF H !9ߠF #!  F0! F F H !9# #݀ #݀ ! ! ! F$F ߀F`H !9݀߀F 0FFH !9 ! #߀ #݀ #݀ # ! ! ! ! FlH !9 ! #߀ #݀ #݀ # F$F$F F D# F,F(#J!!!2 3 F"!!!! !!!!!F!!!!!IF 0FF 0FF 0FF 0F 0FF 0FF 8FF 8FFXGJF0! FF0 ! FF ~## #  FH!9F H!9 F0 FF0 F0 FF0 F D# F 0FF$F d# F 0FF$F 8 FF$F ~FF # FD#߀ F$FH 9FH 9F8ZFF.}#н !!߀!!! FH 9F 0FFXGF80! #!   #!   F DFH 9FH 9N  F,H 9N  #߀ F"8# F 8FF 8FFZ##  # F8! FF FFF0! FF # F0߀! F $F # F80#!  #! ! F$FH 9F"8# F 8FF 8FFx##  # F8! FF 6FFF0! FF # F0߀! F $F # F80#!  #! ! F$FH 9F*8# ߀F 8FF 8FF##  # F8! FF \FFF0! FF # F0߀! F $F .# F80#!  #! ! F$FH 9F8! F 8IFF0! FFH 9FXGF #!  F8II! F 8 F #I F 8IFFH 9F$F0! FF8I! 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H߀ #E݀ FEF$F$F$FFF 98F \F8FFF(8y#!A!E! 3!3! 3!3! 3 F \F Xy FA4 incorrect data FFF 8~FiFF4CON:FFFF$F$F|FFF ! ! ! ! FFFF !FF6PM" "3 Way Analysis of VarianceFF PMcF^PM"LSource Of Variation Degrees of Freedom Mean Square F-Value PercentF PMcFXGFc 4FF8 FP9Fc# ! F4 FP9FF# ! F4 F vFO# ! F 4F# ! F 4F$F F*PM"Due A F$F ߀F *PM"Due B F$F @߀F *PM"Due C F$F F *PM"Due AB F$F ߀F *PM"Due AC F$F ߠF *PM"Due BC F$F XF *PM"Due ABC F$F FC*PM"Due Residuals F$F F PMcF 0McFP9FDF H߀FsFFF$FFF(4 severe error of unknown type FFF  jF߀FfF$F F߀FfF$F FFfF$FF ()#J!!2 3!#3!$3!%3 FF H!I!!!!!s!!FF !& !' !( !) !* FFH& !  !' !(! !) !* F8sF 4$ !F 4% !F8,F (8*#J!! 3!(3!*3!)3!s! FF8+#(3!#3! F  # F3& ! !' !( !) !* FD#߀ F$FXG݀F! N(! FH(!9F$FH$9(! FH%9$ FH 9N(! F ,FXG݀F!XG݀F!   FH#!9#!   F 8FH#!9F$F F FXGJ݀F& ^##!߀! 3 FXG݀F H'9FXIG݀F0! I F0#)I *I FFH'9' #I! F IF FXG݀F H!  9' F <F 8FXG݀F H!  9ߠF F$F XF& ! !' !( !) !* FD# F,F&(*#J!!2 3!+3!*3!)3!! F&H!!I!!!!s!!!! F8sF! 4) !F 4* !FXGJ݀F0 F #  F0 ! 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F4!!! !H!s!!!!I![!!! !F # F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F 4 !F 8 F8HFXGJ݀F90! F 8FF p## # F8HF 8F  F$F &FF8IF #H݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXGF) .#  F 8IFF$F F #I F ,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F8I߀FXG߀F9  F8HFF$F FF F#H݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F 8 F8TFF(8*#J!! 3!43!83!73!s! FF #s F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXGJ݀F9XG݀F9 8  F0! FFH!9#7 8 F3 F# F# 43 !FXG߀F3(8*#J!! 3!+3!*3!)3!s! FF0NJs F #݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXG݀F9H9!9) 8 7 FXIG݀FFH3!I93!I +!I F tIF :F FXG݀FFXG݀FFH4!94! 3! F F F8,#33!+3! F  F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXG݀F9XG݀F90FXIG݀F90+!I 4I! FF IFH3!9F4H6!9F4 F F#!33!+3 FFXG݀FH3!9+! F +! FH3!9F$F vF8 F0F \߀IF V#3!  F 0#3! FH5!9F FF$F F8 u !߀ FXG݀F H5!93! F F #!!&3!63!33!53 FFXG݀F H+!9F0FXG݀F 0H+!݀94! 8 8 F00+!߀ +!݀ F 4F 0N FFXG݀F+.H+!݀9+!߀ F6H+!9+! +!݀ 7 F F F*0 #J# ݀ FXG ߀F"H5!9 05! F&H5!9߀5! F*H5!9# #߀ F85! F#5! ! FH5!9'F FXG ߀FXG߀F0+! FXIG݀F&0+!I߀ 9!I F ªIFH4!9F |F `FXGJ݀F9XG݀F9 8  F0! FFH!98 7 F <F  F 8  F,6 !& !7 !8 !) !* !9 !: !3 ! FD# F,FJ!!2 3!;3!3!3 F FH F!!!!!!I![F 4 !FXGJ݀F3P9FP9FP9FXG݀F3 8  F0! FFX[G ߀F3 #;[! F  F$F [F ĞF$8  F8 F! F FFF FF2(0#J!!!2 3!<3!#3!$3!%3!!! F & ! !+ !' !( !) !* FVH& !  !+! !' !(! !) !* F H!I!!!!!s!!F!!!! F!8sF!0F!4 ## ## # F !+ !' !( !) !* FD#߀ F$FXG݀F#H 9߀F H$9F H%9F F8,F(8*#J!! 3!+3!*3!)3!s! FFߣ =pF!XG݀F)XG݀F)H(!9+! F) ǬF ǐF8+#(3!#3! F 0# F3 & ! !+ !' !( !) !* FD#߀ F$FXG݀F*H$9(! FH%9$ F RFXG݀FF H<9FXG݀FF(H<9< #! #! $ FF FH<9u< ! FH 9+! F ȨF0FXG݀F ɒ#( <  F0( < F$F ɺ# FH+!9< F$F bF 0FF # F0F$F ^F ʈ# ߀ FXG݀FXG݀F"H#!9#! Nw$ ! FF NF 2F$F # F & ! !+ !' !( !) !* FD# F$F ˴#߀ F8FF 8.##3!+3!(3!!! FXG݀F0FXG݀F0+! +! FF ZF H$9FH%9FF 6F$F ̦#߀ F8F ^ FXG݀FFXG݀FF H#!9#! #$ F &F  F$F 8.##3!+3!(3!!! F"#+3!!!#3!(3!$3! FF$FXG݀FH%9$ FXG݀FFH#!9+! FF F F & ! !+ !' !( !) !* FD# F,F"2#3!![!3!43!$3! FF!!!!IF! # FXG[݀F*H$9$ #߀ FF ;F$FXG[݀FXG[݀F0FXIG[݀F"04I! 4I! $I FF VIFIH!9F4 2F FXG[݀FH$9N! F FXG[݀F0FXG݀FH#!9#! $ FF0#! #! FF (F H$9F F= FFF8FFFJT!!.Linear Interpolation: Variable containing DataF .!#н !н !!!!3!8 FiFF j8F \F#A! F \F$FFF!8!DFFF@T!!$Difference: Variable containing DataFi.!#н !н !!!!3!8 FaFF 8F8 F 8DEFF TEFEF$F@T!!$Difference: Variable to place resultFi.!#н !н !!!!3!8 FlFF"  #E݀ F 8EDFF$F$F @8F \F#A!! F$F \FF  F9!!8!DFFFBT!!'Moving Average Variable containing DataF.!#н !н !!!!3!8 FoFF 8F8 F 8DEFF PM" ""Browns 1 Way Exponential SmoothingFF PMcF PMcF8 FP9F#! F4PM" Smoothing coefficient : "F8F#! F PMcF4PM" Standard error of estimate : "FP9F #! Fd PMcF4PM" Projection for next period : "F 0McFF dH߀FeF#!! FF$FFF FH F9!!!!!8!DFrFFRTh!!6Double Exponential Smoothing: Variable containing DataF.!#н !н !!!!3!8 FiFF @8F8 F 8DEFF EFEF$FRTh!!6Double Exponential Smoothing: Variable to place resultF.!#н !н !!!!3!8 FiFF" : #E݀ F 8EDFF$F$F f8F2LY! "Double Exponential SmoothingFF,LY ! "Smoothing Coefficient: FH!9ݐFhH!9߀FnH!9ߠFnH!9߀FnH!9F88F 89FFF `9F0! F F 4 Improper dataFFI 8ZFm \Fr,88 #A! ! !!!3 F  8 F4 improper dataFFi$FFF \Fr4CON:FF#!!3 FFF$F$F$F \F FF!!23 F !F2F>PM" "#Brown's 2 Way Exponential SmoothingF PMcF PMcF8 FP9F#! F4PM" Smoothing coefficient : "F8F#! F PMcF4PM" Standard error of estimate : "FP9F XGFa# ! F PMcF FPM" Projection for ߀  periods on : "F F 0McFF H߀FeF#!!3 F$FFF FH F9!!!!!!8!DFFFRTh!!6Holt's Exponential Smoothing: Variable containing DataF.!#н !н !!!!3!8 FiFF 8F8 F 8DEFF EFEF$FRTh!!6Holt's Exponential Smoothing: Variable to place resultF.!#н !н !!!!3!8 FiFF"  #E݀ F 8EDFF$F$F 8FF2LY! "Double Exponential SmoothingFF6LY ! "!Smoothing Coefficient for level: FH!9ݸFhH!9߀FnH!9ߠFnH!9߀FnH!9F6LY ! "!Smoothing Coefficient for trend: FH!9ݸFnH!9ߠF H!9ߠF H!9߀F H!9F88F 89FFFL 9߀#! !  F 9F0! F0! F. >  ߀F4 Improper dataFFI 8Fm \Fr.88!#A! ! !!!!3 F 8 F4 improper dataFFi$FFF \Fr4CON:FF #!!!3 FFFF$F$F$F \F FFFF !!!23 FF !FF>PM" ""Holt's 2 Way Exponential SmoothingFF PMcF PMcF8 FP9F#! F8PM"# Smoothing coefficient for level: "F#! F PMcF8PM"# Smoothing coefficient for trend: "F8F#! F PMcF4PM" Standard error of estimate : "FP9F XGFa# ! F PMcF FPM" Projection for ߀  periods on : "F F 0McFF H߀FeF #!!!3 FF$FFF FH F(!9!I!p!!!!!!!8!DFFFTT`!!8Winter's Exponential Smoothing: Variable containing DataF .!#н !н !!!!3!8 FtFF 8F8 F 8DEFF EFEF$FTT`!!8Winter's Exponential Smoothing: Variable to place resultF .!#н !н !!!!3!8 FtFF"  #E݀ F 8EDFF$F$F 8F4LY! "Winter's Exponential SmoothingFF6LY ! "!Smoothing Coefficient for level: FH!9ݸFhH!9߀FnH!9ߠFnH!9߀FnH!9F6LY ! "!Smoothing Coefficient for trend: FH!9ݸFnH!9F H!9ߠF H!9߀F H!9F<LY ! "'Smoothing Coefficient for seasonality: FH!9FnH!9߀F H!9ߠF H!9߀F H!9F0LY ! "Initial estimate of level: FH!9ݠF H!9ߠFsH!9߀FsH!9FH!9F0LY ! "Initial estimate of trend: FH!9ݠF H!9FsH!9߀FsH!9FH!9F(LY! "Period of Season: FFH!9ݠFoH!9F H!9F H!9߀F H!9F88F 89FFF 9F0! F0! F0! F8! F4 F I B F0pF 8F 0p5 FF$F4 F XI B F0IF 8nF 0I5 FF$FN ߀߀݀F 4 Improper dataFFI 8Fm \Fr80%#A! ! !!I!p!!!!3 F  ZF4 Improper dataFFI$FFF \Fr4CON:FF #!!!!3 FFF$F$F$F \F FFFF !!!!23 F !FF:PM" "Winter's Exponential SmoothingFF PMcF8 FP9F#! F<PM"' Smoothing coefficient for level: "F#! F PMcF>PM"( Smoothing coefficient for trend: "FF PMcF<PM"' Smoothing coefficient for seasonality:"F8F#! F PMcF4PM" Standard error of estimate : "FP9F PMcFXGFa# ! F FPM" Projection for ߀  periods on : "F F 0McFF H߀FeF #!!!!3 F$FFF ! !; F.H! !; ! ! FI![!!!8!!9!}FFFP9F!6T!!Cross Tabs Select VariablesF.!#н !н !!!!3!} FeFF }F89F8FFFF&LY! "Cross TabulationsF<LY! "Select break points for class  FXGFeH!9Fb(H!9߀݀FoH!9ߐFH!9FH!9F L9FBLY!߀݀ " break point "7߀"F&H!9F 4H!9߀݀F7&H!9ߐFH!9FH!9FL9FBLY,!߀݀ " break point "7F FF88F 89FFF8FF 4 F8F I B FP9݀FFH;!95 F8F$FF$ h߀F F }9߀F 9F \F#A!}!3!;3!3!3 F \F}8IF3F4CON:FFFF #}!I!;3!3!3!3 FIF} I F&8[ w߀! FaFF [7F@LY! !+Warning a yes answer destroys existing dataFH!# Put summary data| in data editor? !! YES | NO !8FF 8߀Fr8[F8FFXG FXIG F.H[!I9݀!I F IF[F FF  F E FXGA݀FX GE߀FH!9ߠF F F$F&8[ w߀! F A[FX[GAFXGE݀FH!9ߠF NF 2F$F 8A[FF8E F$F$F$F$FFF !; ! FF }!I!2;3!3!3!3 F[!J!!F4####FF < FF4#####F$F p FF4######FF$F  FF4#######F$F  FF4########FF$FF#ZPM"& Cross Tab of   vs  FF  F\PM"' for level I߀  of  FF$F PMcFHPM"  " FFPM" "FFX[G FPMc!!7["F <[F PMcF PMcFXG FPMc! ####!7"FX[G F<PMc!!7߀I![߀ "FF [F PMcF F 0McFF nH߀FF #}!I!;3!3!3!3 F$FFF} 8!}FFFPTp!!4Cubic Spline Interpolation: Variable containing DataF.!#н !н !!!!3!8 FnFF 8F \F8}&#A! F \FA } F 4 not appropriate data FFF $F$FFFFF !8!DFrFFPTl!!5Lagrangian Interpolation: Variable containing X DataF.!#н !н !!!!3!8 F FF  8F8 FPTl!!5Lagrangian Interpolation: Variable containing Y DataF.!#н !н !!!!3!8 F FF  8F \F"88##A! ! F \FA  z8 F 4 not appropriate data FFF $F$F$FFFFF ,[!!4!5!>!9!}!!!I!!FV ! ! F"H ! ! FXGF6L9; FACTOR ݀  ! FP9FT  FFF0F4F<T!! Factor Analysis Select VariablesF ,!#н !н !E!!!3!} FVFF d}FXG}݀FL9 F  F  x}FX}GFL9 F  ZF$F,LY ! !Select Type of RotationF8F8F8F89F FF,|d!ߖ!!ߥF,|!ߖ!!ߥF"Tn!ߣ!CANCELFT!ߣ!OKFEFF  <߀FF04!5!>F  >FD  F55ߠ4ߠ4FYFF  8F8F$F FF$FD  5ߐ5߀44FYFF  }F8F$F FF$FD ,554ߠ4ݹFY8F FF$F( 5ߖ5ߥF$ 44F89F$F$ 44F89F$F$F  9 F &FXGFL9 F F$FFF ^9߀F FFFF$LY! "Factor AnalysisF.LY! "Select orthoblique valueFFH!9ߌFtH!9߀FtH!9߀FtH!9߀FtH!9F(LY! "Orthoblique factor F88F 89FFF0! F Fu&4 Value must be from| 0 to .5 FF 89Fm$F f9Fm$F !> !# !$ !% F2H> !#! !$ !% F \F480#A!}!!3!>3!#3!$3!%3!!! F \FA L}F!XGFXGF!H#!9ߠF .}FH#!9ߠF$F F F$F8FF8u! F4CON:FFFF #!!>3!$3!%3 F 8F fF!4 ޾ FACTOR LOADING VARIABLES FF\4 P F8Iw}! F8[w! F 8}FF 8[FF* #!#3!3!3!3![!I!! FFF$F 8vF F$F  ! ! !> !# !$ !% FH7߀! FF FF XF$TP!! ROTATION F(T!! F XF \F&T!! NONE F$F F!&T!! VARIMAX F$F F!&T!! QUARTIMAX F$F (F!&T!! EQUIMAX F$F lF!&T!! ORTHOBLIQUEF$F XF*T(!!COMMUNALITIES F T!! FA XF FT!!NO F 8(FT!!YESF$F XF0T(!ߐ!# FACTORS TO EXTRACT F T!ߐ! FO XF 4 F B ݀F4 FF$FT!ߐ!F XFF !!2>3!$3!%3 F I!F2F,PM" "Factor Analysis FF PMcFNPM"< Factor # Eigen Value Percent Variation EstimatedFPPM"= Covered CommunalityFFXIGFPMc!#####!7I"F6PMc!############.####!7$I߀ "FF:PMc!#################.##!7%I݀ "FF6PMc!############.####!7>I߀ "FF PMcF IF 0McFF 8H߀F#F #!!>3!$3!%3 F$FFF,[!!4!5!>!9!}!!!I!!FF  ! ! ! !# !$ !% F>H ! ! !#! !$E !%E FFF0F4F@T!!%Principle Components Select VariablesF,!#н !н !E!!!3!} FlFF D}FJ!$ Destructive Process | Continue? !! YES | NO !8Fl >8߀Fv \F"8)#A!}!3!#3!$3!%3 FFXG}݀F%6L9; FACTOR ݀  ! FL9 FP9FF F (}FX}GFL9 FL9 FXGFH#!9ߠFH#!9ߠF F F$F \F8FF8u}! F4CON:FFFF#!!$3!%3 F 8F N}F4 ޾ PRINCIPLE COMPONENTS FF\4 P F8Iw}! F8[w}! F 8}FF 8[FF* #!#3!3!3!3![!I!! FFF$F$F ! ! !# !$ !% FH7߀! FF!!2$3!%3 F I!F2F0PM" "Principle ComponentsFF PMcF@PM"- Factor # Eigen Value Percent VariationFF:PM"( CoveredFXIGFPMc!#####!7I"F6PMc!############.####!7$I߀ "FF:PMc!#################.##!7%I݀ "FF PMcF  vIF 0McFF !bH߀F#F#!!$3!%3 F$FFF&[! !8!!}!!!I!!F  ! ! ! !? !4 !5 FRH ! ! !?! !4! !5! F4 !݀FFF0F4F 8Iu!E݀ FNTx!!2Discriminant Analysis Select Independent VariablesF,!#н !н !I!!!3!} FeFF #ZF!JT!!/Discriminant Analysis Select Dependent VariableF*!#н !н !!!}!3!8 FFF$F +(F!P}9 FXG}݀FL߀9 F4L9; FUNCT ݀  ! F #F L9 CONSTANT FL}߀9 FX}GFL9 FL߀9 F $<F \F*8/#A!}!3!?3!43!53! ! FF $ F}4 improper data FF 8+"Fi %4 }߀F!X G}߀FL9 F %F$F % FX GFXGFH?!9ߠFH4!9ߠF %xF %dF$F &@}FX}߀GFXGFH?!9ߠF &F %F$F &FXGFXGFH4!9ߠF &F &pF$F \F8FF8u ! F4CON:FFFF#!!53 F 8F & F 4 ޾ FUNCTION COEFFICIENTS FF\4 P F8Iw !ߘ F 8[w}! F 8}FF 8[FF* #!?3!3!3!3![!I!! FFFXG߀F:L9; CLASS ݀  ! F (F  )FXGFL9 F )bF$F4 ޽ AVERAGE SCORES F\4 P F8Iw}! F 8[w߀! F 8}FF 8[FF* #!43!3!3!3![!I!! FFF$F$FFF ! ! !4 !5 !? FH7߀! 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FF 6# F 0XX߀! F $F0X#X) * FF" 7@## # F0XF$FH!9! XF 6dF0 ! F 7# F "0 ߀! F$F0 # ) * FFH494  F 8 # F0CC N FF$FH!94 FF 5NF9H494   F$F 4LFF(1#23!,3!! F "!!!! !! !X!F!0F 8 FXG݀F! 8FF0F 8FXGF! 9@(! F 8F0(! FF$F 9F 8F 9#(! ݫpǝ FD#߀ F 8;FF :#  F0FpXGF! !! F,! !,! F 9F!$F0! F0X! FXGFH!9X! FH,!9,! XF :FFXG݀FF ;4#  F0X! F ;.#X FFXGF"H!9! X! F"H,!9,! X,! F :F$F$F :F$F 8F 0( FF D# FF,F2(2#!J!!2! 3!53!+3!A3!!!@3 F,!H!!!!s!!!I!! !F ) !* !4 ! ! F<H) !* !4 ! !! F(C! !!!!X!h!+!!2!6!F <###!! 3 ߀ FsF# 8>F#XGF 8  F0! FF ># F 0߀! F $FH)9) F >VF$F =F 8sFs ? ##Js F) !* !4 ! ! FD#߀ F$FXGFH)9) #Js F H5߀!9) F ?6FXGJ߀F8F ?F 8#߀!! 3 F $F @#!! 3 FXGF 8  F0! FF @PFF 0߀! F $F&H*9* #) #) F @F$F ?FXGF @* FH*9N* F 8@FN H*9F$F(H5߀!9* NJs F A,# F H)9F$F @FH5!9F6#! 3!!@3!*3!)3!43!3!3!J!! FF A#߀ FF#$FXG݀F!XGF*H+!9!   #Js FFD0X#!   #Js #!   #Js F Bt#X FH+!9+! NX F$F B#X F!H+!9F$F CX# F&H+!9!  C#Js F<0X#!   #Js #4 CC#Js FF C.#X FH+!9F 8CRFH+!9+! NX F$F$F CFH+!9݀FF$F AF AF0FXGF0(! ߀ F CF DZ߃nOFFXG݀FFXGFH!9+! FF D,F DF$F D# F!XG݀FFH!9! F DF$F8 1#3!@3!! F & E ݫpǝF#) !* !4 ! ! FD#߀ F$FHA 9FF< F<## #߀ ߀wf F 00 FFN0߀#Js#ݠ  F$8#߀ F>#! F prob of not significant mullticollinearity */ HA 9'F 8F`FHA 9ߠF$F F#߀ FH5!9) F $F0hF 8F FF FF$F0* FFXG݀Fi 8IFF G*#߀ FIF#$F,H5߀!9I! * Fn G# F>H5!95! 5߀! ) F$F GF! H#߀ F$H5!9! FF$FHA 9F H`#X:S F2H5!95! #߀ F 8HFH5!9F$F H5!9ߠFHA9F0F0̸F8 ߀ F#!53!J!! 3! FF8HF0 F 8F I2# FJF#$F8FXGJF J#!  F0+! ! FF I# F"0++߀! F$FHA 9A ++F J&#߀ F&0 ++! ߀ F $F Jx#H FHA9A ++F0+XFF0XXFF$F 0X+FF8HFF$F IbFF0F  KZ#A F+,0#A  A FHA 9A F KT#A #++ F"HA 9#A ++ F$F$FHA9F K#߀ FHA 9 F$F 8F KFFFF$F0+4 CC#Js FF&HA9+* * A F0XA F8Js߀F LZ#߀ FF#$F0F02F L#+ F 0A +* * F $F L# F02(X* * F$FXG݀F 8FF M2#߀ FF#$F0h* * F*H5߀!9hN2@! F N# F0FXIG݀F0@!I @!I FF MIF2H5߀!9hN2#@!  F$F MF NZ#߀ F.H5!9* N2@! FF$F N#݀ F0F$FHA9* N2 FHA9F80# #Js݀ F HA9FHA9F On#A vȴ8 F8HA9#A  ##݀A  F $F O#A  FHA9F$FHA9F O#A  FHA9F$FHA9FHA9F PB#A F#A !! F$FHA9'F Q#݀ F"H5!9! FXG݀FHH5!95! 5߀! ! F PF!$F0ϸF Q># F#!53!J!! 3! FF$F8 ߀ F RJ# FHA 9F0F(XGJ݀F0+! ! FF0+! ! FF00߀! ݀! FHA 9A +F0FF QF$F Rz# F HA 9A F$FXGJ߀F>H!  9!  ! FF RF8F&0 #J!  !I! FHA 9IFHA 9FXGJ߀F>H!  9!  ! FF SVF0FXGFB05! *߀ 5! *߀ F SFHA9F TN# F(HA9A A F!$F TA FHA9ߠF$F 8F TFFF$FXG߀FXG߀F 0 * F 0* F U#߀ F UL# F0F 8UlF0*߀ F$F UF0 F 8UF0 *߀ F$F$FH@!9@!  F TF TF W|F0F H5!9#Js FXGFXH5!95! 5! 5! @߀!݀ F W: ߀FXG݀FdH5!95! 5! 5! @߀!݀ F VF!$F V@F!0H5!9A N(5! F$FH5!9߀F() !* !4 ! ! F D# F ,F2(3#!J!2!! 3!53!3!A3!!!@3 F( ! ! !) !* !4 ! !B !C FH ! ! !* !) !4 ! !B݀!߀ !C݀!߀ F<!!!H!!! !!!"!s!!!I!! !F!!!!!X!CF! Y# F 0FF$F 8F8FFXGF H)9F H*9FP9  F YJF 4B !F 4C !F8sFXGJ߀F$ Y#߀#!! 3 F!sF# 8ZI!!J!2 3!@3!53!A3!!!!!(!)!*!+ F"!!!!!!!! !F05! FXGF(0 I!߀ 5! F rF6H I!݀9 I!߀ 5! F$F rLF8F sNFF\IF H I!9 I! F sFH I!9߀F$F0FXG݀F0ܸFXG݀F0 I! @! FF sFI0 I! FF szF t&# F,0N߀߀J A F 8tRF"0N# A F$F 0FF0G{F0G{F u(FF tF0߀JF$F0< F* ubRA waFF80#)!* )!+ A #߀ FF0#߀ F$F(#!߀!J߀ F0'w!' FFH)!(9'F$FF , F(4-!.!/!9!!![!0!8!!}!!!IF!!!!(F @ ! ! ! !A !+ !5 F\H ! ! !@! !A !+! !5! F4 !݀FFF8/F81F8(dFd0F4F 8Iu!E݀ F w@,F 8Iu߸!E݀ F$F w~,F 8Iu߸!E݀ F$F4Multiple Regression FF w,Fs4Ridge Regression F$F x,Fn4Cochran Regression F$F xF,Fi4Huber Regression F$F x,Fn4Weighted Regression FF$F\T#B ݀!!Select Independent VariablesF,!#н !н !I!!!3!} FFF yF!ZT#B ݀!!Select Dependent VariableFF*!#н !н !!!}!3!8 FFF$F {6F!P}9 F 82EFE yE6FEF$FFF\T#B ݀!!Select 'Calculated' VariableF6!#н !н !!!}݀!3!8 FFFP}߀9 FL 9 CalculatedF}" z #E݀ F 8E2F$F 82EFE {0,E6FEF$F$F |n,FFF\T߀#B !!Select 'Weighting' VariableF6!#н !н !!!}݀!3!8 F8FFFP}߀9 F |h,F" |b #E݀ F 8E2F$F$F$FFFH!9ݜFH!9߀FH!9߀FH!9߀FH!9F88F89F FF }|,F&LY! "Ridge RegressionFF$LY! "Ridge factor: FF$F0ǸF },Fg.LY! "Cochran Orcutt RegressionF&LY! "Cochran factor: FF$F ~,Fh&LY! "Huber RegressionFF(LY! "Maximum deviation: FH!9ߴFeH!9߀FeF 89F& ~9߀! F0! F$F b,,FF 89FD 9߀#! !  F$FFF ,F 0! F8F$F ,F0! F  ߀F!8F$F$F$F &9F> #}#6 , }#6߀ F83F ,F3FF$F  ߀F 82EFE E6FEF$FFF8T!!Variable for Lower 95% boundF.!#н !н !!!}3!3!8 F8- FP}39 F3FFL-9 Low 95% F - #E݀ F 8E2F$F 82EFE E6FEF$FFF ^F68T!!Variable for Upper 95% boundF.!#н !н !!!}3!3!8 FFF$FP}39 F3FF8. FL.9 High 95% F . #E݀ F 8E2F$F8/F$F$F  ߀F }#63 F 82EFE ! Do you want a constant? !! YES | NO !8F 88߀F$F \F8F F  FF &, Fn482#!A!}!!3!53!+3!A3!!!@3 F 8`F#084#!A!}!!3!53!+3!A3!!@3 F$F  F4 improper data FF 8Fi4CON:FFFFFFFF /FFFFFT!!*Calculating 95 percent bounds on estimatesF'6T!! and or Cook's DFs \FXGA݀F 8#!}!3 FF ߀F   ߀F H!-9ߠFH!.9ߠF$F 8FXIG}݀F H+!I9!I F &IF!8*}߀ F 8+} FD#!}!A!+3!@3!53!A3!!!!!(!!*!+ F  ߀FH!-9FH!.9F$F$F F9FF \F9$F$F$F 88F F$FFF ! ! !4 !5 !? FH7߀! FF!!253 F I!F2F8PM" "Multiple Regression AnalysisFF8PM" "Dependent Variable } FF PMcFZPM"HVariable Mean Std Err Coefficient Std Err T BetaFXIG݀F PMc!I "FF,PMc! #######.###!75I! "FF,PMc! #######.###!75I! "FF.PMc! #######.#####!75I! "FF |5I! F5,PMc! ######.####!75I! "FF 8FcPM" NA "F$F0F 4 5I! 5I! Fi(0(5I! 5I! F $F N5I! F0F$F ~FPMc!###.###!7"FF 8FcPM" NA "F$F0F #I F0F$F b#I F05}߀! F 2zI>F0F>$F*05I! 5I! F$F F PMc! ######.#####!7"F 8Fc PM" NA "FF$F PMcF IF 0McFF "H߀F F#!!53 F$FFFF F XG}FXG}݀F"*H+!9+߀!݀ F zF ^F$FX}߀GFXGFH+!9ߠF F FX}GFL9 FL9 FXGFH+!9ߠF jF 2F \FXG}݀FL9 FL9 F FL}9} F4 ޾ CORRELATION TABLE FF\4 P F8Iw}! F 8[w}! F 8}FF 8[FF* #!+3!3!3!3![!I!! FL9 CONSTANT FXG}FL9݀ FI FFF8FF"8u}߀! F4CON:FFFF # !& FH#! !& F0F! }߀F0LY! "Calculating Condition indexF8+#+3!#3!} FFF F 0F 0 FFXG}݀Fn D(+! F0(+! FF$F r(+!  F0 (+! FF$F F  ߫pǝFF0N N F$F$F$F # !& F#!!53 F 8F  }FFF4CON:FFFFFFFFF I!FFF8PM" "Multiple Regression AnalysisFF PMcF8 FP9F#A ! F&PM" Standard error FF PMcFP9Ft#A ! F 4FF#A ! F4 R-SQUARED F,4 Adjusted R-Squared FFPM"F PMcF4F VALUE FF#A ! F 4FPM"F PMcF44Degrees of freedom: Numerator A Fs&4 Denominator A F PM"FP9FF#A ! F PMcFFPM"1Percent chance of a higher value; if no relation F PMcF#A ! F.PM"Durbin-Watson statistic FF6PM""Squared deviations due regression "FF A Fe&PMc! #########.###!7A F 8FcPMc! NAFF$F4PM"!Squared deviations due residuals "F ,A Fe&PMc! #########.###!7A F 8HFcPMc! NAFF$FP9F##A ! F<PMc!+Estimated Cochran value for next iteration FP9Ft#A ! FHPMc!6Farrar Glauber Prob of insignificant multicolinearity FF#! F4PMc!"Condition index of data matrix is FF#A ! F A F 4 NAF$FHPMc! # of runs A  Probability of randomness FFP9Fr#A ! F.PMc!Estimate of ridge parameter FF 0McFP9FmF H߀FfFFF$FFF.!!!!9![!0!8!!}!!!IFF @ ! ! ! !A !+ !5 F\H ! ! !@! !A !+! !5! F4 !݀FFF0F4F 8Iu!E݀ FRTd!!7Stepwise Regression Select Trial Independent VariablesF,!#н !н !I!!!3!} FeFF F!HT!!-Stepwise Regression Select Dependent VariableF*!#н !н !!!}!3!8 FFFP}9 F$F F } #E߀ F 82EFE$F E6FEF$FFFLT!!0Stepwise Regression Select 'Calculated' VariableFa6!#н !н !!!}݀!3!8 FlFFP}߀9 FL 9 CalculatedF}"  #E݀ F 8E2F$F$FFF FH!9ݜFH!9߀FH!9߀FH!9߀FH!9FH!9ݜFH!9ߠFH!9߀FH!9߀FH!9F(LY! "Stepwise RegressionF.LY ! "Percent needed to be in: F0LY ! "Percent needed to be out: FF88F 89F F 89Fp 9߀#! ! ! !  FFF0! F0! F \F$F F8F 9F483#!A!}!!3!53!+3!A3!!!@3 FF0ҸF8F482#!A!}!!3!53!+3!A3!!!@3 F h F4 improper data FF 8Fi4CON:FFFFFFFF$F$FFF ! ! !4 !5 !? FH7߀! FFF,'!!!9![!0!8!!}!!!IFF(D !E !@ ! ! ! !A !+ !5 FpH !D !E ! ! !@! !A !+! !5! F4 !݀FFF0F4F 8Iu!E݀ FHT!!,Chow Regression Select Independent VariablesF,!#н !н !I!!!3!} FIFF F!DT!!)Chow Regression Select Dependent VariableF*!#н !н !!!}!3!8 FFF$F @F!P}9 F @} #E߀ F 82EFE$F \E6FEF$FFFHT!!,Chow Regression Select 'Calculated' VariableF6!#н !н !!!}݀!3!8 FdFFP}߀9 F" 4 #E݀ F 8E2F$FFF$F FH!9ݠFH!9߀FH!9߀FH!9߀FH!9F$LY! "Chow RegressionF4LY ! "Number of points in sample 1: FF88F89FF 89F< D9߀#! ! A FFF8'! F \F$F F 9F8F0ǸF885#!A!}!!3!53!+3!A3!!!@3!' F L F4 improper data FF 8zFiFF4CON:FFFFFF$F$FFF$D !E ! ! ! !4 !5 !? FH7߀! FFFF I!FF8 F4PM" "Chow Regression AnalysisFF PMcF2PM" Points in first sample: ' FF PMcF4PMc!F Value calculated: ####.##!7D F PMcF$PM"Degrees of FreedomF8PM" Numerator D FF8PM" Denominator D FF PMcFP9F #D ! F$PM"Percent Chance ofFF.PM" Higher Value F PMcF 0McFP9F F 0H߀FeFFF$FFFF$4![!8!9!!!!!I!F(!5!6!7F84FFF!! Do you want to|estimate values? !! YES | NO !8FF p8߀Fn8IF8[w}! F8F4 ޾ POINT POINT ESTIMATION FF\4 P F4+ !ߠFXG}FL9 F hFL}9 FXGF <L9; ݀  ! F F 8F* #!+3!3!3!3![!I!! FFF6 j}+! +! F 8F+89F+F( +! +! F89F 8~F8(dFd85F86F87FB#!}!A!+3!@3!53!A3!!!!!(!5!6!7 FH+!9FH+!9FH+!9F p ߀F!0/+! F@"H+!9#߀ F!0/+! F"H+!9#߀ F!H+!9ߠF0/+! F"H+!9#߀ F!H+!9ߠF$FF!$F 9߀F 8[F9 8IFFXG}FL9 F FL9 Low 95% FL9 estimateFL9 High 95% FFF* #!+3!3!3!3![!I!! FFF$F 8F84F$F& 4 ݘF!FF8!9![!I!!!!FFFFH!9ݜFH!9߀FH!9FH!9߀FH!9FH!9ݨFH!9ߠFFH!9FFH!9߀FFH!9F88F89F(LY! "Extract Summed DataF&LY! "Starting Number: F(LY! "Period to extract: FF 89F< 9߀#! !  FFF \F8! F8! F$ #݀ A9F8[F8FFXGE݀FAH!9FXIG߀F&H!9! I! F IFH[!9! 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Nature of groups !!INDEPEND | RELATED !F R߀Fo"LThe groups are independentFF 8RF LThe groups are relatedFF$FLFFFeIߠF$F 8XFl!E No of dependent | or | Criterion Variables !! NONE | ONE !FL S߀F (L There are no criterion variablesFF 8SFr$LThere is 1 criterion variableF$FLFFFeIߜ@ F  UF|!E Level of measurement | of | Variables !! NOMINAL | ORDINAL |INTERVAL !F T߀Fo4L,Level of measurement of variables is NominalFF@U8߀Fe4L,Level of measurement of variables is OrdinalFF 8UvFe4L-Level of measurement of variables is IntervalF$FLFFFvIF 8XF~!G Level of measurement | of | Criterion Variable !! NOMINAL | ORDINAL |INTERVAL !F Vx߀F <L5Level of measurement of criterion variable is NominalF@V߀Fe<L5Level of measurement of criterion variable is OrdinalF 8WFe>L6Level of measurement of criterion variable is IntervalFF$FLFFFvIF!H Level of measurement | of | Predictor Variables !! NOMINAL | ORDINAL |INTERVAL !F X߀F >L6Level of measurement of predictor variables is NominalFF@Xb߀Fe>L6Level of measurement of predictor variables is OrdinalFF 8XFe>L7Level of measurement of predictor variables is IntervalF$FLFFFvIF$F$F 0XIFYF4 Chi Square 1 FY8dFa4 Chi Square 1 FYZnFa4 McNemar FYFr4 Chi Square 2 FFYFu4 Cochran Q FYFn*4 Kolmogorov Smirnov | or | Sign FFZLFo(4 Mann Whitney U | or | Median FFZ<VFh4 Wilcoxon FFZfFo4 Kruskal Wallis FFZFl4 Friedman FFZFa4 T Test 1 FFZ4F 4 T Test 2 FFZ>F 4 T Test 3 FF[*F $4 1 way ANOVA | Randomized FF[LFA4 ANOVA FF[F 44* Factor Analysis | with | Dummy variables FF[F 24( Kendall Coefficient | of | Concordance FF[hFl4 Factor Analysis F\.F "4 Contingency Coefficient F\^xFg 4 Discriminant Analysis F\Fm24) Spearman or Kendall | Rank Correlation F\Fa84. Regression Analysis | with | Dummy Variables FF]HFs4 Regression Analysis F <]F0R-! FFH-!9-! FF$F t ݀FFXGFF tF0RR! - F 8tF0RR! -! FF$F ttF@tR F 8FF$F u F H-9RF 8u$FH-!9RF-$F sF\߀IF ujF 0R- F 8uF0R-! 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" Tic Every: FFXGF H!9݀Fc&H!9߀FH!9߀FH!9߀FH!9߀F !F88F 89F "9F0=! F0<! F "&=(! F 0?w?!#<= ߠ F 0>w>!#<=  F$F4F=FFFFFF8F0XF FFFFF8F #HF0TFF$F #F0UFF$FF 2+ FF 9!yF 4,FF 4-+FF89FF 8KB- F8D-!- F $KF89F 4,,-F 8$F"8yC?-!߀! F  $y߀F>4,,;-! (0~?-!߀! )F 8$F;4,,;-! F$F4-=-!K F$F %B- F89FF$F #9߀F 4+,FFF  F8F8nF8oF 8kMB NFN 8mkF8qMNFF*h!2!n!k!o!l!p!m!q F %F! Ν FF 8&F *!!n!k!o!l!p!m!q F$FF0FF 8!FFF4F(LY! "Tic Length SettingFF&LY! "Tic Length (mm): FH!9FH!9߬FhH!9ߠFhH!9ߠFhH!9߀FhH!9߀Fh,LY! "Ratio major to minor: FFH!9FH!9߬FoH!9FoH!9ߠFoH!9߀FoH!9߀Fo88F 89F (t9F0(! F $0w!! Fr$F 0FFFFFFLFFLFFLFF2L+ B/STAT by R. W. WilsonF.L' CopyRight 1989FLFF*L" This program is sharewareFF0L( suggested contribution is 30.00FFLFF0L) Contributions should be sent to FLFF&L 2677 Council Ring Rd,FF,L$ Mississauga Ontario L5L 1S6FFL CANADAFLFFLFFBL: The file may be copied and distributed as long asFFBL: no amount is charged for the copy and the READ.MEFF"L file is included.FF `F FDDDD D(D0D8D@DHDPDXD`DhDpDxDDDDDDDDDDDDDDDDEEEEE E(E0E8E@EHEPEXE`EhEpExEEEEEEEEEEEEEEEEFFFFF F(F0F8F@FHFPFXF`FhFpFxFFFFFFFFFFFFFFFFGGGGG G(G0G8G@GHGPGXG`GhGpGxGGGGGGGGGGGGGGGGHHHHH H(H0H8H@HHHPHXH`HhHpHxHHHHHHHHHHHHHHHHIIIII I(I0I8I@IHIPIXI`IhIpIxIIIIIIIIIIIIIIIIJJJJJ J(J0J8J@JHJPJXJ`JhJpJxJJJJJJJJJJJJJJJJKKKKK K(K0K8K@KHKPKXK`KhKpKxKKKKKKKKKKKKKKKKLLLLL L(L0L8L@LHLPLXL`LhLpLxLLLLLLLLLLLLLLLLMMMMM M(M0M8M@MHMPMXM`MhMpMxMMMMMMMMMMMMMMMMNNNNN N(N0N8N@NHNPNXN`NhNpNxNNNNNNNNNNNNNNNNOOOOO O(O0O8O@OHOPOVO\ObOhOnOtOzOOOOOOOOOOOOOOOOOOOOOOPP PPPP"P(P.P4P:P@PFPLPRPXP^PdPhPlPpPtPxP|PPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPPQQQQ QQQQQ Q$Q(Q,Q0Q4Q8Q<Q@QDQHQLQPQTQXQ\Q`QdQhQlQpQtQxQ|QQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQRRRR RRRRR R$R(R,R0R4R8R<R@RDRHRLRPRTRXR\R`RdRhRlRpRtRxR|RRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRRSSSS SSSSS S$S(S,S0S4S8S<S@SDSHSLSPSTSXS\S`SdShSlSpStSxS|SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSTTTT TTTTT T$T(T,T0T4T8T<T@TDTHTLTPTTTXT\T`TdThTlTpTtTxT|TTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTTUUUU UUUUU U$U(U,U0U4U8U<U@UDUHULUPUTUXU\U`UdUhUlUpUtUxU|UUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUUVVVV VVVVV V$V(V,V0V4V8V<V@VDVHVLVPVTVXV\V`VdVhVlVpVtVxV|VVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVVWWWW WWWWW W$W(W,W0W4W8W<W@WDWHWLWPWTWXW\W`WdWhWlWpWtWxW|WWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWWXXXX XXXXX X$X(X,X0X4X5X6X7X8X9X:X;X<X=X>X@XFXLXRXXX^XdXjXpXvX|XXXXXXXXXXXXXXXXXXXXXYYY YYYY$Y*Y0Y6Y<YBYHYNYTYZY`YfYlYrYxY~YYYYYYYYYYYYYYYYYYYYYZZZZZZ Z&Z,Z2Z8Z>ZDZJZPZVZ\ZbZhZnZtZzZZZZZZZZZZZZZZZZZZZZZZ[[ [ [[[[[[[,358:b=?ZDG"P2~>PrdTX >R/\''{p-20Z3?xD68:=JdL. X$--NG~Nr`&ae u.|v^wRyz"Ǣ6z{B|&} Bb2|nx0ðŠZ݈"nt x.:.lZR$NҪpӂԖT :ْr8t 6 j(:d0JˊЎt&tT^|~x |Yn{vcth8 !np&sx,|tŊ>puD.`,NXlpϒzv30+./b-j0569p:=AZCExKLSPTUXp]l`:_ flrHy6N ?JJLfNKMMNOjnpty.~snww\x"+p2gc.bd<q.<,ЦF՜&z5Bb~dFf &"<^؀:Lnא\*״ jvv vr&3h$,!&<12Lpi<M.8%B\z@\z`x:IDL@ A@>EvENj*0$|2 &D 2BtVFh|:6Jx]T_bnv*,(h&#VZ "D"n`t"%.([["[([.[4[:[@GF8"> 6v 88&( t.0 178?BFFP\]_dgikz^Xo^r8d;tWjZn<-6t\(\(S } Rbeqr6yv[]"^~_algjjkkmp:py@[NhNhhiriknnoBp vv***There are some known bugs in this program at present. The author tells me that they have been removed from the most current version of the program which is being prepared for compilation. In the graphics component, don't use the log scaling, and you may find the redraw graph/floating labels to not print floating labels when you go back to a previous menu even though every thing appears fine on the screen. However, it is easy to work around these problems.**** B/STAT is a sophisticated graphing and statistical analysis program. At present it is in interpreted GFA Basic. As such it is still highly useable because of the speed of the interpreter. It will be in compiled form some time in the summer of 1989 and will be uploaded to the various boards at that time. B/STAT is being distributed as shareware. The cost for BSTAT is 30.00 but the user will get a 160 page document of which 90 pages serves as a statistics tutorial as well as the compiled version when the GFA compiler is available. The compiled version will not be posted on any BBS. The Atari community is rather well known for not contributing to shareware. In the case of this program that approach could well turn out to be a mistake. The program is very powerfull and utilizing the full features can take some support. Support will only be forthcoming to registered users. As well the compiled version will only be available to registered users. B/STAT requires 1 megabyte and a double sided drive. The author can be reached on CIS # 72355,1637 or at the address given on startup of the program. The author assumes no responsibility for errors in the program. Indeed I guarantee that there are errors. Some mine and some GFA's Upon de Arcing there will be 2 additional ARC files. One of these contains on line help support and the other the GFA run time package.  Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 1 2 3 Dl Dh Dl Dh Dl Dh 15 1.08 1.36 .95 1.54 .82 1.75 16 1.10 1.37 .98 1.54 .86 1.73 17 1.13 1.38 1.02 1.54 .90 1.71 18 1.16 1.39 1.05 1.53 .93 1.69 19 1.18 1.40 1.08 1.53 .97 1.68 20 1.20 1.41 1.10 1.54 1.00 1.68 21 1.22 1.42 1.13 1.54 1.03 1.67 22 1.24 1.43 1.15 1.54 1.05 1.66 23 1.26 1.44 1.17 1.54 1.08 1.66 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 1 2 3 Dl Dh Dl Dh Dl Dh 24 1.27 1.45 1.19 1.55 1.10 1.66 25 1.29 1.45 1.21 1.55 1.12 1.66 26 1.30 1.46 1.22 1.55 1.14 1.65 27 1.32 1.47 1.24 1.56 1.16 1.65 28 1.33 1.48 1.26 1.56 1.18 1.65 29 1.34 1.48 1.27 1.56 1.20 1.65 30 1.35 1.49 1.28 1.57 1.21 1.65 35 1.40 1.52 1.34 1.58 1.28 1.65 40 1.44 1.54 1.39 1.60 1.34 1.66 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 1 2 3 Dl Dh Dl Dh Dl Dh 45 1.48 1.57 1.43 1.62 1.38 1.67 50 1.50 1.59 1.46 1.63 1.42 1.67 55 1.53 1.60 1.49 1.64 1.45 1.68 60 1.55 1.62 1.51 1.65 1.48 1.69 65 1.57 1.63 1.54 1.66 1.50 1.70 70 1.58 1.64 1.55 1.67 1.52 1.70 75 1.60 1.65 1.57 1.68 1.54 1.71 80 1.61 1.66 1.59 1.69 1.56 1.72 85 1.62 1.67 1.60 1.70 1.57 1.72 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 1 2 3 Dl Dh Dl Dh Dl Dh 90 1.63 1.68 1.61 1.70 1.59 1.73 95 1.64 1.69 1.62 1.71 1.60 1.73 100 1.65 1.69 1.63 1.72 1.61 1.74 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 4 5 Dl Dh Dl Dh 15 .69 1.97 .56 2.01 16 .74 1.93 .62 2.01 17 .78 1.90 .67 2.01 18 .82 1.87 .71 2.01 19 .86 1.85 .75 2.01 20 .90 1.83 .79 1.99 21 .93 1.81 .83 1.96 22 .96 1.80 .86 1.94 23 .99 1.79 .90 1.92 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 4 5 Dl Dh Dl Dh 24 1.01 1.78 .93 1.90 25 1.04 1.77 .95 1.89 26 1.06 1.76 .98 1.88 27 1.08 1.76 1.01 1.86 28 1.10 1.75 1.03 1.85 29 1.12 1.74 1.05 1.84 30 1.14 1.74 1.07 1.83 35 1.22 1.73 1.16 1.80 40 1.29 1.72 1.23 1.79 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 4 5 Dl Dh Dl Dh 45 1.34 1.72 1.29 1.78 50 1.38 1.72 1.34 1.77 55 1.41 1.72 1.38 1.77 60 1.44 1.73 1.41 1.77 65 1.47 1.73 1.44 1.77 70 1.49 1.74 1.46 1.77 75 1.51 1.74 1.49 1.77 80 1.53 1.74 1.51 1.77 85 1.55 1.75 1.52 1.77 Critical Values of the Durbin Watson Statistic 5 Percent Significance no of no of independent variables points 4 5 Dl Dh Dl Dh 90 1.57 1.75 1.54 1.78 95 1.58 1.75 1.56 1.78 100 1.59 1.76 1.57 1.78 Friedman Test Approximate Critical Values No of No of variables Points 3 4 5% 1% 5% 1% 2 NA NA 6.0 NA 3 6.0 NA 7.0 8.5 4 6.3 7.8 7.6 9.5 5 6.1 8.3 6 6.4 8.5 7 6.1 8.8 8 6.2 9.0 9 6.2 8.7 The main menu area is used for travelling between menus and for loading and creating files. "Creating files" first requests information on the type of label to be used for the data. These labels are used only for graphing, and have no impact on the statistical procedures in the program. They may be initialized as blanks to be filled in later by you. They may simply be a counter, in which case you will be asked to specify the starting value and a rate of increment. This option would be used if you wanted to specify calendar years, such as 1988. You may select months as a label. In this case, you must enter a numeric value for the month, such as 1 for January, etc. The data may be specified as days of the week or weekdays. The difference between these two is that days of the week includes Saturday and Sunday, while week days includes only Monday to Friday. For each of these options, you have 13 different ways in which the date may be shown. These are displayed in a grid of 27 squares on the screen. Clicking the mouse button on one of the squares will highlight the style. A subsequent click will return the square to normal. Clicking on OK will make the choice official. This style of dialog box is used throughout B/STAT for selecting variables. Pressing the "F1" key will have the same effect as pressing OK. Pressing the "F2" key will cancel the operation, and the default or previous labels will remain. In other procedures "F2" will also act as a cancel button. After selecting the style, you must specify the date information about the starting day for the data. These values must be specified numerically. The week is assumed to start on Monday, so 1 is Monday and 7 is Sunday. If you enter an impossible month, such as month 23, the program will take the modulus of 12 and this number to generate the starting month. Similar actions occur for the day and the day of the week. Years may be entered as 1988 or as simply 88. Any number below 100 is treated as 1900+ the number; any negative numbers are converted to positives, so, unfortunately, years such as 34 B.C. will have to be typed as manual labels. Once the type of label is entered, you will move to the spreadsheet style data entry screen. This screen allows for 26 columns of data, and as many rows as you initialized in the program. The minimum number of data rows is 19. B/STAT is not a spreadsheet. This screen is simply for data entry, although some facility for variable creation does exist. The spreadsheet uses both drop-down menus and commands for operation. For rapid movement around the spreadsheet the ">" command is used. >s45 will move the cursor to column "S" and row 45 automatically. As well, there are commands for sorting columns, adding them together, etc. The command list is available by selecting the help menu from the data entry screen. For missing data, enter NA as the value. The normal view of the columns in the spreadsheet is as separate data variables. There are statistical procedures in B/STAT, however, which treat the entire collection of data as a matrix of data. These procedures are discussed more fully in the manual and in the individual help screens. B/STAT can save and load different data formats. -"Save" and "load" do so in B/STAT's format. -"DIF load" and "DIF save" do so in the data interchange format introduced by VISICALC many years ago and currently supported by most programs. B/STAT will ask you if you want to load the data by column or row. Strictly speaking, the question is misleading. In the original DIF standard you could save the data by row or by column. Many programs today give you no such choice, so you cannot tell whether the variables were saved as rows or columns. Similarily, B/STAT cannot tell whether the data represents 12 variables with 20 points each, or 20 variables with 12 points each. We suggest that you load data by column and then check to see if you got what you wanted. If not then simply type "FLIP". The program will switch the rows and the columns. Note that B/STAT can accept only numeric data in a DIF file. -An ASCII file refers to a file in which each record is a number. To be used by B/STAT the data must be in the following order: #rows used; #columns used; data value for col 1 row 1; data value for col 2 row 1; data value for col 3 row 1; etc. -PRN files are created by many spreadsheet programs. These are actual disk images of pages which would otherwise have been printed. Only numerics are allowed in B/STAT. The data must have been saved in such a way that the columns represent data variables. -WKS files are produced by products such as LOTUS 123. They may also be labelled as WK1 files. To load these you must specify a range from the spreadsheet. This range will be stated as A23-F47 for example. Only numeric data will be accepted. If you already have data in B/STAT, you will be asked if you want to replace the existing data or to augment it by creating new variables for the new data. -SYLK files are created by multiplan. In all respects the dialogs are the same as for WKS files. Editing a file simply places you in the spreadsheet data editor without destroying the existing data. This allows for adding or changing data. The help drive selection allows you to change the drive path for finding the help files. When you start the program, the drive searched for the files is the one from which the program was started. The "Tables" selections load in standard statistics tables so that you can check values against them. Not all possible tables are present. Tables are not used for tests where B/STAT is able to calculate the probability by direct mathematical means. Coach poses a series of questions. Your answers to these will enable the program to suggest statistical procedures. Not all processes available in B/STAT are referenced by "Coach". For example, time series studies are not suggested. This is because coach was designed for a different class of problem than is addressed by time series. As well, some of the procedures in B/STAT are not, in and of themselves, statistical procedures. Interpolation, fourier smoothing, etc., are not really statistical in nature but simply mathematical. To use "Coach", you must have some knowledge about your data and of terms used. The tutorial should give these to you. The first question asks about the number of variables measured for the experimental units. If, for example, you are studying data on cars and you measure the price of each car, then you have measured 1 variable. If you measure gas mileage and acceleration as well, then you have measured 3 variables. If you want to measure the influence of acceleration and gas mileage on price, then price would be considered the dependent, or criterion variable, and acceleration and gas mileage are the independent variables. If you don't want to assume a dependency relationship, then there would be no dependent or criterion variable. In such a case, you would only be looking for relationships among the variables. The succeeding questions will deal with the nature of the variables themselves, to determine whether they are nominally, ordinally, or intervally scaled, and whether they are related or not. At the end of the questions (3 or 4 generally), the program will return a suggested procedure. In some cases, there is none. Remember that one can consider intervally scaled data to be ordinally scaled, and you may wish to do so for some types of analysis. 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<3Ho">3XoDFf,3XHf<3XsHL0Nug">3Xl Ff,3HXf<3HsXL0Nu>3X||F`Case without SelectSelect without EndselectMll - Editor FehlerWhile without WendRepeat without UntilDo without LoopFor without nextWend without WhileUntil without RepeatLoop without DoNext without ForIf without EndifEndif without IfElse without IfElse without EndifExit without loopProcedure without ReturnProcedure in loopProcedure redefinedFunction without EndfuncFunction in loopFunction redefinedReturn without ProcedureLabel redefinedLocal without ProcedureLocal in loopFunction redefinedGoto into/outof For-Next, Procedure or FunctionResume in For-NextResume without ProcedureResume in FunctionEndfunc without FunctionNew VariableNew ProcedureNew FunctionNew label[2][Ask on new names ?][Yes|No] New names [2][Clear Inline ?][Ok|Error]Division by zeroOverflowNot Integer|-2147483648 .. 2147483647Not Byte|0 .. 255Not Word|-32768 .. 32767Square root only|for positive numbersLogarithm only for|numbers greater than zeroUndefined error Out of memory Function or command|not yet implemented String too long|max. 32767 characters Not GFA-BASIC 3.00 program Program too long|memory full|NEW Not GFA-BASIC program|file too short|NEWArray dimensioned twiceArray not dimensionedArray index too largeDim index too largeWrong number of indicesProcedure not foundLabel not foundOn Open only|"I"nput "O"utput "R"andom|"A"ppend "U"pdate|allowedFile already openFile # wrongFile not openInput wrong|not numericEnd of file reachedToo many points for|Polyline/Polyfill/Polymark|max. 128Array must have|one dimensionNumber of points too|large for arrayMerge - Not an ASCII fileMerge - Line too long|aborted ==> Syntax error|program aborted!Undefined label"Out of data#Data not numeric%Disk full&Command not allowed|in direct mode'Program error|Gosub not possible(Clear not allowed in|For-Next-loops or|Procedures)Cont not possible*Parameter missing+Expression too complex,Undefined function-Too many parameters.Parameter wrong|must be a number/Parameter wrong|must be a string0Open "R"|Record length wrong1Too many "R"-files (max 31)2Not an "R"-File4Fields larger|than record length6GET/PUT|Field string length changed7GET/PUT|Record number wrongMENU error?RESERVE error@Pointer (*x) errorAArray too small (<256)BNo VAR-ArrayCASIN/ACOS ErrorDVAR-Type mismatchEENDFUNC without RETURNGIndex too largeZLOCAL error[FOR error\Resume (next) not possible|Fatal, For or Local]Stack ErrordGFA BASIC Version 3.02 U| Copyright 1986-1988|GFA Systemtechnik GmbHf2 bombs - bus error|Peek or Poke possibly wrongg3 bombs - address error|Odd word address! Possibly at|Dpoke, Dpeek, Lpoke or Lpeekh4 bombs - illegal instruction|executed in machine codei5 bombs - divide by zero|in 68000 Machine Codej6 bombs - CHK exeption|68000 interrupted by CHKk7 bombs - TRAPV exeption|68000 interrupted by TRAPVl8 bombs - privilege violation|by 68000 Machine Codem9 bombs - trace exeptionGeneral errorDrive not readyUnknown commandCRC error|disk check sum wrongBad requestSeek error|track not foundUnknown media|boot sector wrongSector not foundOut of paperWrite faultRead faultGeneral error 12Write protectedMedia change detectedUnknown deviceBad sector (verify)Insert other disk|(request)Invalid function numberFile not foundPath not foundToo many open filesAccess deniedInvalid handleOut of memoryInvalid memory block addressInvalid drive specificationNo more filesGEMDOS range error|seek wrong?GEMDOS internal errorInvalid executable file formatMemory block growth failure[1][Do you really want to quit?][Yes|No][1][Program end][Return][2][Stop program ?][Stop|Cont][2][Printer listing ?][Yes|No][2][NEW - Kill program ?][Yes|No] Syntax Error Line too longAsOkH 6&* & "$ rR  0tb8,8&Z`FV &tH  < $,~l(X"6@( ^$0N,D 4d xN ,  2"0:PF @xhvN T &20J X0& NjH GRAPHICS Graph menu The REGULAR selection will place along the "X" axis of your graph the labels you have entered in the data entry area of the data editor spreadsheet. The type of graph will depend on the selections you have made in the "styles" area. Up to 6 variables may be chosen. You may plot some using the left axis and some using the right axis. The HORIZONTAL graph option puts the labels on the "Y" axis and the values along the "X". You cannot have a right side axis for this type of graph. "XY" graphs allow up to 6 pairs of variables to be used. You must select your data a pair at a time. The first one chosen of each pair will be the "X" value of the point and the second will be the "Y". You may repeat the same selection between pairs so that you can have several variables graphed against the same "X". There are no XY bar graphs. You cannot have a right side axis. HI LO graphs are stock market graphs. The first 3 variables chosen will be displayed as a high-low-close type of graph. The remainder of the 6 possible graphs will be shown as selected on the styles section. You can use right side axis which allows you to graph volume on the same graph as stock prices. You can have a High Low graph with only 2 variables. In this case the data represents simply a high and low, but no close. PIE CHARTS. You may have up to 4 pies on the screen. Simply specify the correct number of variables. A special case exists for 2 pie charts, if you have selected "component pies" from the features menu. In this case the second variable will be assumed to be an explosion of the first pie segment. BUBBLE GRAPHS require 3 variables to be chosen. The first specifies the "X" value of the point, the second specifies the "Y" value of the point, and the third specifies the relative area of the bubble. OPPOSED BARS require 2 sets of opposite variables which must be positive. If the "log" selection is on it is ignored. Opposed bars are good for comparing similar data against one another. An example might be the population of the U.S.A. by age group, where one variable represents males and another females. The key feature of opposed bars is that there is no offset between the variables. A peculiarity of the implementation comes up in rescaling. Since the second variable is treated as negative by the program, the minimum value is shown as a negative. This is a requirement, so be certain to enter the minimum as a negative value, even though it will be printed as positive. FLOATING BARS require 2 variables for each bar plotted. The first represents the minimum of the floating bar and the second, the top. As with XY graphs, you will continue to be prompted for input until you fail to enter 2 variables. This is not an XY graph, however. The X-axis is scaled by the labels, just as for a regular graph. HORIZONTAL FLOATING BARS are the same as regular floating bars, except that the graph is done horizontally. POLAR PLOTS are a variation on XY graphs. Selection procedures are the same. The difference is that the variables chosen give the angle in radians, and distance of the point rather than "X" and "Y" respectively. 3D BARS allow for up to 40 points in each factor, and display the data with a three dimensional aspect. The variables are displayed behind one another, with the first variable chosen being the front variable. In some cases, data points will not be seen since the column will be entirely hidden. No right side scaling may be used. STAT GRAF These procedures are particular graph types used for analysis. A STAR GRAPH produces a chart describing the physical values of several variables at each of several points. There should be no negative values. For each point, a series of lines are drawn starting at 3 o'clock and then working counterclockwise around the point. The length of the lines represents how high the value of the variable is for that point. The minimum value of the line is set to 20 percent of the maximum. A SUN RAY GRAPH is similar in concept to the star graph. In this case, each line is the same length, but the line is cut at a value indicating relative length. If the line is cut exactly in the middle, then the point has a value for that variable which is at the mean for all points. A BOX WHISKER GRAPH requires the selection of a variable and a category variable. The box and whisker are then drawn for values from the first variable where the categorical variable is at a certain level. The box and whisker is a regular style graph. The box has its top value at the 3rd quartile point and its bottom at the first quartile. The box is bisected by a line at the median. Extending out from the box at top and bottom are the whiskers. These reach out to the highest and lowest point in the data variable for a given level of the categorical variable. The NOTCHED BOX WHISKER is the same except that there is an additional piece of information given. There is a notch in the box which covers a 95 percent confidence limit on the median. The depth of the notch is proportional to the number of elements in the variable with that value of the categorical variable. XYZ graphs are similar to XY graphs. The main difference is that there are three coordinate axes, and you must pick the variables in threes. Another change is the lack of a legend. No legend is put on the right of the graph to allow for the extra width taken by the three dimensional graph. For labelling you will need to use the custom labelling feature. For XYZ graphs you may select point, line and bar options. The bar option does not actually produce bars in this situation. Instead, a perpendicular is dropped to the XY plain. This gives a better indicator of the height of the point. Z function plots are three dimensional graphs of a function of the form Z=f(X,Y). You will be asked to specify the graphing limits for X,Y and Z. You will then be asked to specify the equation and then the number of steps to make in each of the X and Y directions. The greater the number of steps, the finer the graph but also the slower the graph. With 50 steps in each direction there are 5000 calls to the parser and this can be a slow process. After setting the parameters you will be asked whether you want hidden lines or not. The default is for no hidden lines (ie a wire frame). The next option is a combination of the previous 2. The main use for this option is to examine actual points from a regression against the 3D regression surface provided by the computer. The Z Data plot assumes that all of the data in the editor represents Z values for particular combinations of X and Y which are uniformally spaced. It does not know what the minimum and maximum X and Y values are. You will be asked to specify the maximum and minimum for X,Y, and Z just as for a function plot. You will not need to specify the number of steps since that is determined by the amount of data available. As an example consider a select mortality table as used by an insurance company. There would be rates of mortality for each issue age and for each of the first 15 durations since the policy was issued. If we were to examine mortality rates for ages 15 to 75 and for durations 1 to 15 the data would be set up as follows. There would be 15 columns in use. Each row in the column would represent the mortality level at a given age for that duration. There would be 61 rows to handle the various ages. The number of steps would internally be set to 60 and 14 with this data. For all of the XYZ graph types the "right side" title is used to label the "Y" axis. SETTINGS The settings menu allows you to define how the graph will look. The palette setting allows you to set the palette for the graph. User Fill allows you to define up to 6 fill patterns for use by the program. These may be saved and reloaded for the next use of B/STAT. They are not compatable with fill files from DEGAS. Styles allows setting the line style fill pattern and point style. It also allows you to turn on lines, bars, or points. All 3 can be on for any given variable. Pie Style allows you to set colors and fill styles for pies, as well as whether a slice is exploded. Background allows for setting a background fill pattern over which the graph is drawn. There are two types of fill, Full and Partial. For Full, the entire graph area is filled in. For Partial, only the part of the graph between the axis lines is filled in. The selection of fill style is the same as for pie or bar styles. Axes allows turning scaling or axes on and off, as well as selecting the color to be used. Titles allows you to enter the titles to be used on the graph. Title Fonts allows you to select the color and style of the main title and the subtitle. Features Boxed means that for regular and horizontal graphs a line will be drawn to close in the graph. Rt side axis will allow a right side axis on regular graphs. Stacked will give stacked bar graphs, and area graphs for line graphs. Filled will cause the area between lines to be filled in. It cannot be combined with stacked. Vals Above will cause the value of the point to be displayed above it for regular and horizontal graphs. For pie charts, the values will be printed below the pie label. Legend will cause the legend for each variable to be displayed. If turned off, then the graph will be larger but you will have to use custom labelling to define what the variables are. Log X causes the X axis to be on a LOG basis. Log Y does the same for the Y axis. Proportional Pie means that if more than one pie is shown on the screen at once, their relative sizes will be determined by the total of the values in each pie. This is quite useful when comparing four years of sales data. Component Pie. When two variables are selected for a pie graph, this option causes the second variable to be taken as a subset of the first pie sector. The values in the second variable are displayed as a stacked bar set to the right of the pie. Pie Percent will cause the percentage each pie slice represents to be printed in the pie slice. The percent is rounded to the nearest whole percentage. Grids These two options turn on horizontal and vertical grids. There is also a "zero line" option to ensure that a line is drawn at the zero point even if no grids are displayed. While a graph is on screen, labels may be added by double-clicking where you want them to appear. You will be required to select the font and size for the label, just as for titles. You have the option of adding an arrow. Simply click where you want it to point. These labels may be dragged on the screen. To remove a floating label, double click on the label. You are now asked, "What to Change?". This can be either font, text, or arrow. You can remove the label by selecting text, and erasing the existing text. A label with no text is simply removed from the list of labels. If you choose arrow you can either add an arrow, if one does not exist, or move the anchor point for an existing arrow, or remove the arrow. You may also resize the graph. This is done by placing the mouse in the lower right corner of the graph and then dragging the mouse. The graph can be reduced to 1/4 its original size. You may also reposition the smaller graph by holding down the mouse button while the mouse is inside the axes. The menu bar displayed while a graph is on screen allows you to save or print the graph. The "Save" menu items allow two forms of saving the screen image. The first is as a DEGAS compatible uncompressed image. The second is as an ".IMG" file, which can be used by desktop publishing programs. With a color system you will be asked if you want a color IMG file. Many desk top publishing programs cannot handle a color file, so you can put out a monochrome version of the screen. The IMG files produced by B/STAT are compatable with IMG files on MSDOS machines. They can therefore be used with Wordperfect version 5.0 on these machines. Note that IMG files are bit image files. The quality of reproduction is not as good as using a GDOS print to the same physical size area. The third choice is as a metafile. Metafiles can be read by programs such as Easy Draw and many desktop publishing programs such as Pagestream and Calamus. I have been unable to get the files to work with the Timeworks Desktop publisher When printing, you have three options. First, you can print the screen using the built-in Atari screen dump utility or one which you have loaded yourself. The second option is useful only for 9 pin Epson printers. This option uses the Epson plotter mode to ensure properly scaled pictures. It also only works with the monochrome monitor. The third choice uses GDOS, if you have it, to plot to the printer. The text on the graph will not usually look quite the same as on the screen, since many GDOS fonts are proportional and the default screen fonts are not. Also, some of the printer fonts are not quite the same size as the screen fonts. The remaining choices are to adjust GDOS printing. The GDOS settings item allows you to decide on the width and height of the graph on the paper. Various GDOS drivers as well as printers will start graphs in different places. Thus, setting the starting position offset to be zero may not put the graph at exactly the edge of the paper. Many Epson-compatible printers start graphics 1/4 of an inch from the edge. You should therefore do a GDOS print of a graph with the standard settings. Before doing the print turn on "GDOS box". This will result in a box being drawn around the edges of the graphing area. You can then use the resulting positions to establish a vertical and horizontal offset for your particular printer. The "GDOS Device" Selection allows you to set the device ID that the program uses to that which you have set in your ASSIGN.SYS file. Most users will never have to use this setting. The default in B/STAT is device 21 which is the usual standard. This choice is for those lucky individuals who have more than one printer in use, or who have a plotter which is supported by GDOS. "GDOS Rotate" allows you to print the graph in landscape mode as opposed to the normal portrait orientation. The miscellaneous menu contains only three unusual feature. The "Keep Labels" option when chosen (the default) ensures that the custom labels will be kept when you return to the graph selection screen. To get rid of them all, simply deselect the option. The legend box selection alows you to move the legend from the right of the screen to other locations. Simply select the option and then drag the object to the desired location. Move legend allows you to move the legend box once you are using one. 25 3 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 population starts ind 4 5 5 2.2 0.0909 0.03635 2.222 0.08942 0.03345 2.244 0.09755 0.0387 2.267 0.0955 0.03745 2.28 0.09678 0.04063 2.289 0.10327 0.04237 2.289 0.10513 0.04715 2.29 0.1084 0.04883 2.299 0.10822 0.04836 2.3 0.10741 0.0516 2.3 0.10751 0.04879 2.34 0.11429 0.05523 2.386 0.11048 0.0477 2.433 0.11604 0.05282 2.482 0.11688 0.05473 2.532 0.12044 0.05531 2.58 0.12125 0.05898 2.605 0.1208 0.06267 2.631 0.12368 0.05462 2.658 0.12679 0.05672 2.684 0.12996 0.06674 2.711 0.13445 0.06451 2.738 0.13325 0.06313 2.766 0.13863 0.06573 2.793 0.13964 0.07229 Critical Values of Kolmogorov-Smirnov Statistic No of Significance Level Points 10% 5% 1% 1 .950 .975 .995 2 .776 .842 .929 3 .642 .708 .829 4 .564 .624 .734 5 .510 .563 .669 6 .470 .521 .618 7 .438 .486 .577 8 .411 .457 .543 9 .388 .432 .514 10 .368 .409 .486 11 .352 .391 .468 Critical Values of Kolmogorov-Smirnov Statistic No of Significance Level Points 10% 5% 1% 12 .338 .375 .450 13 .325 .361 .433 14 .314 .349 .418 15 .304 .338 .404 16 .295 .328 .391 17 .286 .318 .380 18 .278 .309 .370 19 """""""""""""""""""" Critical Values of Spearman Rank Correlation Test One Tail Test No of Significance Level Points 5% 1% 4 1.00 NA 5 .90 1.000 6 .829 .943 7 .714 .893 8 .643 .833 9 .600 .783 10 .564 .746 -The data editor is designed for efficient entry of data for further analysis. -Data will be in the form of variables, with a column for each variable. -Commands are issued either through the menu or from the keyboard on the command line. -The first set of commands deals with columns. These allow you to insert a column, blank a column, or delete columns. If you choose the "Del Many" option you will be asked for the number of columns to delete. That number of columns, starting at the column in which the cursor resides and moving to the right, will be removed. Blanking a column does not remove it but just erases the data. -You may either load or save an individual column, as well. This allows you to save a data variable from one data set and bring it into another. -The actions available for rows are the same as those for columns, except that you cannot save or load a row. One additional row operation is available. The "delete Marked" option checks the value of each row in the coluill be displayed as a high-low-close type of graph. The remainder of the 6 possible graphs will be shown as selected on the styles section. You can use right side axis which allows you to graph volume on the same graph as stock prices. You can have a High Low graph with only 2 variables. In this case the data represents simply a high and low, but no close. PIE CHARTS. You may have up to 4 pies on the screen. Simply specify the correct number of variables. A special case exists for 2 pie charts, if you have selected "component pies" from the features menu. In this case the second variable will be assumed to be an explosion of the first pie segment. BUBBLE GRAPHS require 3 variables to be chosen. The first specifies the "X" value of the point, the second specifies the "Y" value of the point, and the third specifies the relative area of the bubble. OPPOSED BARS require 2 sets of opposite variables which must be positive. If the "log" selection is on it is ignored. Opposed bars are good for comparing similar data against one another. An example might be the population of the U.S.A. by age group, where one variable represents males and another females. The key feature of opposed bars is that there is no offset between the variables. A peculiarity of the implementation comes up in rescaling. Since the second variable is treated as negative by the program, the minimum value is shown as a negative. This is a requirement, so be certain to enter the minimum as a negative value, even though it will be printed as positive. FLOATING BARS require 2 variables for each bar plotted. The first represents the minimum of the floating bar and the second, the top. As with XY graphs, you will continue to be prompted for input until you fail to enter 2 variables. This is not an XY graph, however. The X-axis is scaled by the labels, just as for a regular graph. HORIZONTAL FLOATING BARS are the same as regular floating bars, except that the graph is done horizontally. POLAR PLOTS are a variation on XY graphs. Selection procedures are the same. The difference is that the variables chosen give the angle in radians, and distance of the point rather than "X" and "Y" respectively. 3D BARS allow for up to 40 points in each factor, and display the data with a three dimensional aspect. The variables are displayed behind one another, with the first variable chosen being the front variable. In some cases, data points will not be seen since the column will be entirely hidden. No right side scaling may be used. STAT GRAF These procedures are particular graph types used for analysis. A STAR GRAPH produces a chart describing the physical values of several variables at each of several points. There should be no negative values. For each point, a series of lines are drawn starting at 3 o'clock and then working counterclockwise around the point. The length of the lines represents how high the value of the variable is for that point. The minimum value of the line is set to 20 percent of the maximum. A SUN RAY GRAPH is similar in concept to the star graph. In this case, each line is the same length, but the line is cut at a value indicating relative length. If the line is cut exactly in the middle, then the point has a value for that variable which is at the mean for all points. A BOX WHISKER GRAPH requires the selection of a variable and a category variable. The box and whisker are then drawn for values from the first variable where the categorical variable is at a certain level. The box and whisker is a regular style graph. The box has its top value at the 3rd quartile point and its bottom at the first quartile. The box is bisected by a line at the median. Extending out from the box at top and bottom are the whiskers. These reach out to the highest and lowest point in the data variable for a given level of the categorical variable. The NOTCHED BOX WHISKER is the same except that there is an additional piece of information given. There is a notch in the box which covers a 95 percent confidence limit on the median. The depth of the notch is proportional to the number of elements in the variable with that value of the categorical variable. XYZ graphs are similar to XY graphs. The main difference is that there are three coordinate axes, and you must pick the variables in threes. Another change is the lack of a legend. No legend is put on the right of the graph to allow for the extra width taken by the three dimensional graph. For labelling you will need to use the custom labelling feature. For XYZ graphs you may select point, line and bar options. The bar option does not actually produce bars in this situation. Instead, a perpendicular is dropped to the XY plain. This gives a better indicator of the height of the point. Z function plots are three dimensional graphs of a function of the form Z=f(X,Y). You will be asked to specify the graphing limits for X,Y and Z. You will then be asked to specify the equation and then the number of steps to make in each of the X and Y directions. The greater the number of steps, the finer the graph but also the slower the graph. With 50 steps in each direction there are 5000 calls to the parser and this can be a slow process. After setting the parameters you will be asked whether you want hidden lines or not. The default is for no hidden lines (ie a wire frame). The next option is a combination of the previous 2. The main use for this option is to examine actual points from a regression against the 3D regression surface provided by the computer. The Z Data plot assumes that all of the data in the editor represents Z values for particular combinations of X and Y which are uniformally spaced. It does not know what the minimum and maximum X and Y values are. You will be asked to specify the maximum and minimum for X,Y, and Z just as for a function plot. You will not need to specify the number of steps since that is determined by the amount of data available. As an example consider a select mortality table as used by an insurance company. There would be rates of mortality for each issue age and for each of the first 15 durations since the policy was issued. If we were to examine mortality rates for ages 15 to 75 and for durations 1 to 15 the data would be set up as follows. There would be 15 columns in use. Each row in the column would represent the mortality level at a given age for that duration. There would be 61 rows to handle the various ages. The number of steps would internally be set to 60 and 14 with this data. For all of the XYZ graph types the "right side" title is used to label the "Y" axis. SETTINGS The settings menu allows you to define how the graph will look. The palette setting allows you to set the palette for the graph. User Fill allows you to define up to 6 fill patterns for use by the program. These may be saved and reloaded for the next use of B/STAT. They are not compatable with fill files from DEGAS. Styles allows setting the line style fill pattern and point style. It also allows you to turn on lines, bars, or points. All 3 can be on for any given variable. Pie Style allows you to set colors and fill styles for pies, as well as whether a slice is exploded. Background allows for setting a background fill pattern over which the graph is drawn. There are two types of fill, Full and Partial. For Full, the entire graph area is filled in. For Partial, only the part of the graph between the axis lines is filled in. The selection of fill style is the same as for pie or bar styles. Axes allows turning scaling or axes on and off, as well as selecting the color to be used. Titles allows you to enter the titles to be used on the graph. Title Fonts allows you to select the color and style of the main title and the subtitle. Features Boxed means that for regular and horizontal graphs a line will be drawn to STATS 1 MENU NORMALITY TESTS These two tests check whether a variable is drawn from a normal population. In both cases, you must select the variable to operate on. In the case where you know the parameters, you will be asked for the mean and standard deviation of the underlying population. The program will not evaluate the statistic returned. Published tables must be used. DESCRIPTIVE STATISTICS These tests provide mean, standard deviation, kurtosis, etc., for the data set. If using grouped data, you will have to select a grouping variable as well as the data variable. CORRELATION These provide simple correlation tests. -Simple correlation is the correlation between two variables which you choose. -The Spearman rank correlation test compares the ranks of two sets of variables rather than the actual numbers. -The contingency coefficient test compares two variables on a parametric basis. Data must be non-negative and scaled nominally. -Kendal Concordance is used with three or more variables which are in the form of ranks. No selection of variables is made. The entire set of data in memory is used. -The Kendal Tau test is similar to the Spearman rank test. It is used for two variables in the form of ranks. -The Point Biserial correlation test is used with two related variables. One variable is at least intervally scaled, and the other is a dichotomous variable. A dichotomous variable is one which can have only two values 0 or 1, such as for male versus female. You will be asked separately for the two variables. -Lagged Auto correlation determines the correlation of a variable with itself at an earlier time. The program will ask for the variable to be examined and a variable into which to store the results. The result is a series of values specifying the correlation for a multitude of lag periods. The first value is with no lag and has value 1. -Lagged Multiple Correlation is similar to the above except that two variables are examined. In this case, you are asked for two variables. Order of selection is important. The lag period will refer to the value of the second variable "K" periods earlier. Thus, if Variable "A" is to be related to Variable "B" at earlier periods, you should select Variable "A" first and "B" second. ORDINAL TESTS -Kolmogorov-Smirnov test checks a single variable to determine if the values support the hypothesis that the differences between them are chance. -Mann Whitney "U" test requires two independent samples (variables). The variables do not have to be the same size. The test determines whether there is a difference in the rankings between two groups. Small values are extreme for this test so the comparison is "is the value less than the table value?" -Wilcoxon test is similar to the Mann Whitney, except that it uses related or paired variables. Like the Mann Whitney, small values are extreme. Thus if the calculated value is less than the tabular value you reject the null hypothesis that there is no difference between samples. -Kruskal Wallis test uses all data in the data set. There must be at least three variables. The test is basically the three-or-more- factor equivalent of Mann Whitney. The extreme values are high, unlike the Mann Whitney. -Friedman test uses all the data. This is the three-or-more-factor equivalent of Wilcoxon. However, because of the formulation, the statistic extreme values are high. -Median test indicates whether the two samples appear to be drawn from populations with the same median. -Runs test is used for one variable. In addition, you must select the test criteria from among zero, the mean, and the median. The test determines whether the data appears to be randomly distributed about the criterion. -Sign test is used to test the probablility that a given variable has a median of some test value. You must choose a variable and then a test value for the median. NOMINAL TESTS -Chi Square 1 test uses two variables, with theis less than 6 and c is greater than 12 Another example is (exp(a)-exp(-a))/(exp(a)+exp(a)) This formula is actually the formula for TANH(a) which would accomplish the same thing. >axx Causes the cursor to go to column "a" row "xx" flip Swaps the rows and columns of the data matrix. Cursor movements can be made using the arrow keys. Holding down the "Control" or "Shift" key and pressing the arrow keys causes movement of a full page. If you hold down both the "Control" and "Shift" keys simultaneously and press an arrow key then you will go to the end of the data in that direction. sort(a) Sorts column a in ascending order. Y is unused sortall(a,b,c) Sorts whole data set with keys a,b,c. Not all keys are needed, but at least 1 must be used bl STATS 2 MENU ITEMS DISTRIBUTIONS This set of items calculates probabilities for the given distribution based upon values which you input in response to questions. No data variables are used. -T-Tests There are three T-tests available. Test 1 calculates the chance that a given variable has a certain mean. You are asked to choose a variable and to specify a mean to test. The second test checks the chance that two variables have the same mean. You have to select two variables. The two variables should be randomly selected and unrelated. The third T test is designed for two variables which are related. Once again you simply select two variables. -Multivariate There are two somewhat similar procedures: Factor analysis and Discriminant analysis. For factor analysis, you first select the variables which you want in the study. You must then select the type of rotation desired. If you choose an orthoblique rotation, then an orthoblique factor must be entered. The orthoblique factor must be from 0 to 0.5. In discriminant analysis, you must first select the independent variables. You next choose the dependent variable. In both procedures the data entry screen is used to display results. No text input can be made, but all menu functions and arrows work. -ANOVA The Analysis of Variance section allows for flexibility in data structure. The one-way studies all require that the data be set up in a traditional ANOVA matrix structure. Questions will not be asked for the random, blocked, or latin square designs. For nested, you will be asked to specify the number of treatments in a block. For the 2- and 3-way ANOVA designs, either the data can be set up in a matrix (the default), or separate variables can be used to represent the levels of the variables. In a 3-way design not using matrices, you would be asked for the variable that held the results and then, in turn, for the variable containing the level information for factors A, B, and C. For data in matrix form, you would need to specify the number of levels in A and B. For the 2- factor case the input required is similar. -Variance Tests The 1-factor test asks for a variable name and a value to test. The value tested is the standard deviation and the program will give back the chance of the variable was chosen from a population with the given standard deviation. The 2-factor test compares two variables to determine the chance that they are both drawn from a population with the same standard deviation. STATS 3 MENU REGRESSION For the tests that follow, all except LOGIT regression have similar input and output structures. You will be asked for the variables that are the independent variables and for the one dependent variable. You will then be asked for the variable (column) into which the calculated values should be placed. The program does not place the residuals in variable (column) a, as this would restrict the number of variables which could actually be used in the regression. To get the residuals, simply subtract the calculated data from the actual in the data editor. The differences lie in additional parts of the regressions. -Multiple regression is a traditional regression. -Ridge regression will require the entry of a ridge factor, which should be small and between 0 and 1 (most often below .2). -Stepwise regression is like multiple regression, except that you specify all independent variables to be considered. The program decides on which of The orthoblique factor must be from 0 to 0.5. In discriminant analysis, you must first select the independent variables. You next choose the dependent variable. In both procedures the data entry screen is used to display results. No text input can be made, but all menu functions and arrows work. -ANOVA The Analysis of Variance section allows for flexibility in data structure. The one-way studies all require that the data be set up in a traditional ANOVA matrix structure. Questions will not be asked for the random, blocked, or latin square designs. For nested, you will be asked to specify the number of treatments in a block. For the 2- and 3-way ANOVA designs, either the data can be set up in a matrix (the default), or separate variables can be used to represent the levels of the variables. In a 3-way design not using matrices, you would be asked for the variable that held the results and then, in turn, for the variable containing the level information for factors A, B, and C. For data in matrix form, you would need to specify the number of levels in A and B. For the 2- factor case the input required is similar. -Variance Tests The 1-factor test asks for a variable name and a value to test. The value tested is the standard deviation and the program will give back the chance of the variable was chosen from a population with the given standard deviation. The 2-factor test compares two variables to determine the chance that they are both drawn from a population with the same standard deviation. pothesis that there is no difference between samples. -Kruskal Wallis test uses all data in the data set. There must be at least three variables. The test is basically the three-or-more- factor equivalent of Mann Whitney. The extreme values are high, unlike the Mann Whitney. -Friedman test uses all the data. This is the three-or-more-factor equivalent of Wilcoxon. However, because of the formulation, the statistic extreme values are high. -Median test indicates whether the two samples appear to be drawn from populations with the same median. -Runs test is used for one variable. In addition, you must select the test criteria from among zero, the mean, and the median. The test determines whether the data appears to be randomly distributed about the criterion. -Sign test is used to test the probablility that a given variable has a median of some test value. You must choose a variable and then a test value for the median. NOMINAL TESTS -Chi Square 1 test uses two variables, with theis less than 6 and c is greater than 12 Another example is (exp(a)-exp(-a))/(exp(a)+exp(a)) This formula is actually the formula for TANH(a) which would accomplish the same thing. >axx Causes the cursor to go to column "a" row "xx" flip Swaps the rows and columns of the data matrix. Cursor movements can be made using the arrow keys. Holding down the "Control" or "Shift" key and pressing the arrow keys causes movement of a full page. If you hold down both the "Control" and "Shift" keys simultaneously and press an arrow key then you will go to the end of the data in that direction. sort(a) Sorts column a in ascending order. Y is unused sortall(a,b,c) Sorts whole data set with keys a,b,c. Not all keys are needed, but at least 1 must be used blreach out to the highest and lowest point in the data variable for a given level of the categorical variable. The NOTCHED BOX WHISKER is the same except that there is an additional piece of information given. There is a notch in the box which covers a 95 percent confidence limit on the median. The depth of the notch is proportional to the number of elements in the variable with that value of the categorical variable. XYZ graphs are similar to XY graphs. The main difference is that there are three coordinate axes, and you must pick the variables in threes. Another change is the lack of a legend. No legend is put on the right of the graph to allow for the extra width taken by the three dimensional graph. For labelling you will need to use the custom labelling feature. For XYZ graphs you may select point, line and bar options. The bar option does not actually produce bars in this situation. Instead, a perpendicular is dropped to the XY plain. This gives a better indicator of the height of the point. Z function plots are three dimensional graphs of a function of the form Z=f(X,Y). You will be asked to specify the graphing limits for X,Y and Z. You will then be asked to specify the equation and then the number of steps to make in each of the X and Y directions. The greater the number of steps, the finer the graph but also the slower the graph. With 50 steps in each direction there are 5000 calls to the parser and this can be a slow process. After setting the parameters you will be asked whether you want hidden lines or not. The default is for no hidden lines (ie a wire frame). The next option is a combination of the previous 2. The main use for this option is to examine actual points from a regression against the 3D regression surface provided by the computer. The Z Data plot assumes that all of the data in the editor represents Z values for particular combinations of X and Y which are uniformally spaced. It does not know what the minimum and maximum X and Y values are. You will be asked to specify the maximum and minimum for X,Y, and Z just as for a function plot. You will not need to specify the number of steps since that is determined by the amount of data available. As an example consider a select mortality table as used by an insurance company. There would be rates of mortality for each issue age and for each of the first 15 durations since the policy was issued. If we were to examine mortality rates for ages 15 to 75 and for durations 1 to 15 the data would be set up as follows. There would be 15 columns in use. Each row in the column would represent the mortality level at a given age for that duration. There would be 61 rows to handle the various ages. The number of steps would internally be set to 60 and 14 with this data. For all of the XYZ graph types the "right side" title is used to label the "Y" axis. SETTINGS The settings menu allows you to define how the graph will look. The palette setting allows you to set the palette for the graph. User Fill allows you to define up #a000000 #b000000 #c7770007000600070055200505552220770557075055507703111103 #d #E FB 02 #W 00 00 0A 01 18 16 08 A:\*.*@ #W 00 00 0D 08 2A 0B 00 @ #W 00 00 0E 09 2A 0B 00 @ #W 00 00 0F 0A 2A 0B 00 @ #M 00 00 00 FF A FLOPPY DISK@ @ #M 00 01 00 FF B FLOPPY DISK@ @ #T 00 03 02 FF TRASH@ @ #F FF 04 @ *.*@ #D FF 01 @ *.*@ #G 03 FF *.APP@ @ #G 03 FF *.PRG@ @ #F 03 04 *.TOS@ @ #P 03 04 *.TTP@ @ rbyyou.Theymaysimplybea counterinwhichcaseyouwillbeaskedtospecifythestarting valueandarateofincrement.Thisoptionwouldbeusedifyou wantedtospecifycalendaryearssuchas1988.Youmayselectmonths asalabel.Inthiscaseyoumustenteranumericvalueforthe monthsuchas1forJanuaryetc.Thedatamaybespecifiedasdays oftheweekorweekdays.Thedifferencebetweenthese2isthatdays oftheweekincludesSaturdayandSunday,whileweekdaysincludes onlyMondaytoFriday.Foreachoftheseoptionsyouhave13 differentwaysinwhichthedatemaybeshown.Thesearedisplayed inagridof27squaresonthescreen.Clickingthemousebuttonon oneofthesquareswillhilightthestyle.asubsequentclickwill returnthesquaretonormal.ClickingonEXITwillmakethechoice official.ThisstyleofdialogboxisusedthroughoutB/STATfor selectingvariables. Afterselectingthestyleyoumustspecifythedateinformation aboutthestartingdayforthedata.Thesevaluesmustbespecified numerically.TheweekisassumedtostartonMondayso1isMonday and7isSunday.Ifyouenteranimpossiblemonthsuchasmonth23 theprogramwilltakethemodulusof12andthisnumbertogenerate thestartingmonth.Similaractionsoccurforthedayandthedayof theweek.Yearsmaybeenteredas1988orassimply88.Anynumber below100istreatedas1900+thenumber;anynegativenumbersare convertedtopositivessounfortunatelyyearssuchas34BCwillhave tobetypedasmanuallabels. Oncethetypeoflabelisenteredyouwillmovetothe spreadsheetstyledataentryscreen.Thisscreenallowsfor26 columnsofdataandasmanyrowsasyouinitializedintheprogram. Theminimumnumberofdatarowsis19.B/STATisnotaspreadsheet. Thisscreenissimplyfordataentryalthoughsomefacilityfor variablecreationdoesexist.Thespreadsheetusesbothmenudrop downsandcommandsforoperation.Forrapidmovementaroundthe spreadsheetthe">"commandisused.>s45willmovethecursorto column"S"androw45automatically.Aswelltherearecommandsfor sortingcolumns,addingthemtogetheretc.Thecommandlistis availablebyselectingthehelpmenufromthedataentryscreen.For missingdataenterNAasthevalue. Thenormalviewofthecolumnsinthespreadsheetisas separatedatavariables.Therearestatisticalprocedureshoweverin B/STATwhichtreattheentirecollectionofdataasamatrixof data.Theseproceduresarediscussedmorefullyinthemanualandin theindividualhelpscreens. B/STATallowsforsavingandloadingdifferentdataformats. StraightsaveandloaddosoinB/STAT'sformat.DIFloadandsave dosointhedatainterchangeformatintroducedbyVISICALCmany yearsagoandcurrentlysupportedbymostprograms. B/STATwillaskyouifyouwanttoloadthedatabycolumnor row.Strictlyspeakingthequestionismisleading.Intheoriginal DIFstandardyoucouldsavethedatabyroworbycolumn.Many programstodaygiveyounosuchchoicesoyoucannottellwhether thevariablesweresavedasrowsorcolumns.Similarilyneithercan B/STAT.Itcannotknowwhetherthedatarepresents12variables with20pointseachor20variableswith12pointseach.Wesuggest thatyoutryloadingdatabycolumnandthencheckingtoseeifit cameinproperly.Ifnotthenreloadbyrow.Fromthenonyouwill knowthatdatafromthatprogrammustbeloadedintoB/STATinthat fashion.NotethatB/STATcanacceptonlynumericdatainaDIF file. AnASCIIfilereferstoafilewhereeachrecordisanumber. TobeusedbyB/STATthedatamustbeinthefollowingorder #rowsused #columnsused datavalueforcol1row1 datavalueforcol2row1 datavalueforcol3row1 etc PRNfilesarecreatedbymanyspreadsheetprograms.Theseare actualdiskimagesofpageswhichwouldotherwisehavebeenprinted. OnlynumericsareallowedinB/STAT.Thedatamusthavebeensaved insuchawaythatthecolumnsrepresentdatavariables. Editingafilesimplyplacesyouinthespreadsheetdataeditor withoutdestroyingtheexistingdata.Thisalowsforaddingor changingdata. Thehelpdriveselectionallowsyoutochangethedrivepath forfindingthehelpfiles.Uponstartingtheprogramthedrive searchedforthefilesistheonefromwhichtheprogramwas started. The"Tables"selectionsloadinstandardstatisticstablesso thatyoucancheckvaluesagainstthem.Notallpossibletablesare present.TablesarenotusedfortestswhereB/STATisableto calculatetheprobabilitybydirectmathematicalmeans. Thedataeditorisdesignedforefficiententryofdatafor furtheranalysis. Dataisassumedtobeintheformofvariableswhicheach occupyacolumn. Variousoperationscanbeperformedonthevariablesby enteringcommandsonthecommandline. Thefirstgroupaffectthevariableinwhichthecursorislocated. AssumethatvariableYcontainsthecursor.Theoperationsare: a+bVariableYisthesumofvariablesaandb a+xVariableYisthesumofvariableaandconstantx a-b a-x a/bVariableYequalsvariableadividedbyvariableb a/xa*bVariableYequalsvariableatimesvariableb a*x a^bVariableYequalsvariableatothepowerofvariableb a^xVariableYequalsatopowerofconstantx abVariableYis1ifagreaterthanbelse0 a>xVariableYis1ifagreaterthanconstantx a\bVariableYisminimumofaandb a\xVariableYisminimumofaandconstantx a|bVariableYismaxofaandb a|xVariableYismaxofaandconstantx a!bSwapsvariablesaandb.Yisnotaltered a!xSetsvariableatovaluex a@xVariableYisaccumulationofaatx%interest paymentsatendofperiod a&xVariableYisaccumulationofaatx%interest paymentsatstartofperiod a@bVariableYisaccumulationofaatinterestratesgiven incolumnb a&bsameasa@bbutpaymentsatstart a$xVariableYispresentvalueofpaymentsat interestratex%paymentsatendofperiod a$bsameexceptvaryinginterestgiveninb a#xAsfora$xexceptpaymentsatstart a#bAsfora$bexceptpaymentsatstart a%xfindsinternalrateofreturnsuchthatPV ofcolumnaequalsxpaymentsatendofperiod a%bFindsaseriesofyieldratessuchthatthePV ofcolumnaequalsthevalueincolumnb TheresultsgoinY RADTODEG(a)VariableYisconversionofatodegrees degtorad(a)VariableYisconversionofatoradians sort(a)sortsvariableainascendingorderYunused sortall(a,b,c)sortswholedatasetwithkeysa,b,c notallkeysneededbutatleast1 counterxxVariableYisfilledwithacounterfrom1to xx blankVariableYisblankedout mult(a)VariableYisrunningproductofa rot(a)VariableYisrotateda fact(a)variableYisfactorialofa abs(a)VariableYisabsolutevalueofa sqr(a)VariableYissquarerootofa sin(a)VariableYissinofa cos(a)VariableYiscosofa tan(a)VariableYistanofa asin(a)VariableYisarcsinofa asec(a)VariableYisarcsecantofa acos(a)VariableYisarccosofa atn(a)VariableYisarctanofa log(a)VariableYislogofa exp(a)VariableYisetothepowerofa log10(a)VariableYislogtobase10ofa exp10(a)VariableYis10tothepowerofa int(a)VariableYisintegerpartofa asinh(a)VariableYisarchyperbolicsinofa acosh(a)VariableYisarchyperboliccosofa atanh(a)VariableYisarchyperbolictanofa sinh(a)VariableYishyperbolicsinofa cosh(a)VariableYishyperboliccosofa tanh(a)VariableYishyperbolictanofa amort(amount,term,conv,payts,intr) amortizesaloanofamount"amount"over aperiodof"term"years. interestisconvertible"conv"timesperyear thereare"payts"paymentsperyear(iemonthlyis12) theinterestrateisspecifiedinpercentby"intr" >axx Thiscommandcausesthecursortogotocolumn"a"row"xx" Cursormovementscanbemadeusingthearrowkeys.Holdingdownthe "Control"keyandpressingthearrowkeyscausesmovementofafull page. STATS1Menu NormalityTests These2testcheckwhetheravariableisdrawnfromanormal population.Inbothcasesyoumustselectthevariabletooperate on.Inthecasewhereyouknowtheparametersyouwillbeaskedfor themeanandstandarddeviationoftheunderlyingpopulation.The programwillnotevaluatethestatisticreturned.Publishedtables mustbeused DescriptiveStatistics Thesetestsprovidemean,standarddeviation,kurtosisetcfor thedataset.Ifthedataisgroupedyouwillhavetoselecta groupingvariableaswellasthedatavariable. Correlation Theseprovidesimplecorrelationtests.Simplecorrelationis thecorrelationbetween2variableswhichyouchoose.TheSpearman rankcorrelationtestcomparestheranksof2setsofvariables ratherthantheactualnumbers.Thecontingencycoefficienttest compares2variablesonaparametricbasis.Datamustbenon negativeandscalednominally KendalConcordanceisusedwith3ormorevariableswhichareinthe formofranks.Noselectionofvariablesismade.Theentiresetof datainmemoryisused. TheKendalTautestissimilartotheSpearmanranktest.Itisused for2variablesintheformofranks. ThePointBiserialcorrelationtestisusedwith2related variables.Onevariablerepresentstheresultandtheotherthe classificationbasedonadichotomousvariable.Adichotomous variableisonewhichcanhaveonly2values0or1.Forexample maleversusfemale.Youwillbeaskedseparatelyforthe2 variables. LaggedAutocorrelationdeterminesthecorrelationofa variablewithitselfatanearliertime.Theprogramwillaskfor thevariabletobeexaminedandavariableintowhichtostorethe results.Theresultisaseriesofvaluesspecifyingthecorrelation foramultitudeoflagperiods.Thefirstvalueiswith0lagand hasvalue1. LaggedMultipleCorrelationissimilartotheaboveexceptthat 2variablesareexamined.Inthiscaseyouareaskedfor2 variables.Orderofselectionisimportant.Thelagperiodwill refertothevalueofthesecondvariable"K"periodsearlier.Thus ifVariable"A"istoberelatedtoVariable"B"atearlierperiods, youshouldselectVariable"A"firstand"B"second. OrdinalTests KolmogorovSmirnov Checksasinglevariabletodetermineifthevaluessupportthe hypothesisthatthedifferencesbetweenthemarechance. MannWhitney Requires2independentsamples(variables).Thevariablesdo nothavetobethesamesize.Thedatarepresentsaranking.Thetest determineswhetherthereappearstobeadifferencebetweenthe samples.Smallvaluesareextremeforthistestsothecomparison is"isthevaluelessthanthetablevalue?" Wilcoxontest SimilartotheMannWhitneyexceptthatthesamplesare related.LiketheMannWhitney,smallvaluesareextreme.Thusif thecalculatedvalueislessthanthetabularvalueyourejectthe nullhypothesisthatthereisnodifferencebetweensamples. KruskalWallistest Forthistestalldatainthedatasetisused.Theremustbe atleast3variables.Thetestisbasicallythe3ormorefactor equivalenttoMannWhitney.Theextremevaluesarehighunlike theMannWhitney. Friedmantest Alldataisused.Thisisthe3ormorefactorequivalentto theWilcoxontest.Howeverbecauseoftheformulationofthe statisticextremevaluesarehigh. Mediantest 2variablesareselected.Thetestindicateswhetherthe2 samplesappeartobedrawnfrompopulationswiththesamemedian. Runstest Thistestisusedfor1variable.Inadditionyoumustchoose whetherthetestcriteriaiszero,themeanorthemedian.Thetest determineswhetherthedataappearstoberandomlydistributedabout thecriteria. Signtest Youmustchooseavariableandthenatestvalueforthe median.Theprogramcalculatesaprobabilitythatthechosenvalue isindeedthemedianofthepopulationfromwhichthedatais selected. NominalTests ChiSquare1 2Variablesareusedwiththefirstrepresentingtheexpected andthesecondtheactual.Thetestdetermineswhethertheactual dataisconsistantwiththeexpected ChiSquare2 Thistestusesallofthedata.Thedataisassumedtobeset upinacontingencymatrixform.Thenullhypothesisisthatthere isnorelationshipbetweentherowsandcolumns. McNemartest Alldataisused.Theremustbe2rowsand2columns.Itisa testusedtoinvestigatechangesinresponseinapreandpost stimulousstudy.Seethemanualfordatasetup. Cochrantest Alldatainthedatasetisused.Theremustbe3ormore relatedvariables.Thedataisdichotomousinnature.InB/STAT positivesaretreatedas1negativesor0as0.Thetestusesthe nullhypothesisthatthereisnodifferencebetweenvariables.STATS 2MENUITEMS Distributions Thissetofitemscalculatesprobabilitiesforthegiven distributionbaseduponvalueswhichyouinputinresponseto questions.Nodatavariablesareused. TTests Thereare3T-testsavailable.Test1calculatesthechancethat agivenvariablehasacertainmean.Youareaskedtochoosea variableandtospecifyameantotest.Thesecondtestchecksthe chancethat2variableshavethesamemean.Youhavetoselect2 variables.The2variablesshouldberandomlyselectedand unrelated.ThethirdTtestisdesignedfor2variableswhichare related.Onceagainyousimplyselect2variables. Multivariate Thereare2proceduresFactoranalysisand Discriminantanalysis.Thesearesomewhatsimilar.Forfactor analysisyoufirstselectthevariableswhichyouwantinthestudy. Youmustthenselectthetypeofrotationdesired.Ifyouchoosean orthobliquerotationthenanorthobliquefactormustbeentered.The orthobliquefactormustbefrom0to.5 Indiscriminantanalysisyoumustfirstselecttheindependant variables.Younextchoosethedependantvariable. Inbothproceduresthedataentryscreenisusedtodisplay results.Notextinputcanbemadebutallmenufunctionsandarrows work. ANOVA TheAnalysisofVariancesectionallowsforflexibilityindata structure.Theonewaystudiesallrequirethatthedatabesetup inatraditionalANOVAmatrixstructure.Questionswillnotbeasked fortherandom,blockedorlatinsquaredesigns.Fornestedyou willbeaskedtospecifythenumberoftreatmentsinablock. Forthe2and3wayANOVAdesignsthedatacanbeeithersetup inamatrix(thedefault)orseparatevariablescanbeusedto representthelevelsofthevariables.Ina3waydesignnotusing matricesyouwouldbeaskedforthevariablethatheldtheresults andtheninturnforthevariablecontainingthelevelinformation forfactorsABandC.Ifthedatawasinmatrixformyouwouldneed tospecifythenumberoflevelsinAandB. Forthe2factorcasetheinputrequiredissimilar. VarianceTests Theonefactortestasksforavariablenameandavalueto test.Thevaluetestedisthestandarddeviationandtheprogram willgivebackthechanceofthevariablewaschosenfroma populationwiththegivenstandarddeviation.The2factortest compares2variablestodeterminethechancethattheyareboth drawnfromapopulationwiththesamestandarddeviation.  STATS3MENU Regression Thefirst7itemsallhavesimilarinputandoutputstructures. Youwillbeaskedforthevariableswhicharetheindependent variablesandforthe1dependentvariable.Youwillthenbeasked forthevariableintowhichthecalculatedvaluesshouldbeplaced. Theprogramdoesnotplacetheresidualsinavariableaasthiswould restrictthenumberofvariableswhichcouldactuallybeusedinthe regression.Togettheresidualssimplysubtractthecalculateddata fromtheactualinthedataeditor.Thedifferencesliein additionalpartsoftheregressions.TheMultipleregression selectionisatraditionalregression.Ridgeregressionwillrequire theentryofaridgefactorwhichshouldbesmallandbetween0and 1(mostoftenbelow.2) StepwiseregressionislikeMultiple,exceptthatyouspecify allindependentvariablestobeconsidered.Theprogramdecideson whichofthesetoactuallyuseintheregression. CochranreferstoaregressiondoneusingtheCochran-Orcutt procedure.A"Cochran"factorofbetween0and1mustbeused.This typeofregressionactuallyusesapartofthepreviouspointinthe calculation.IftheCochranfactoris1thentheregressionis actuallycalculateduponthefirstdifferencesofthevariables. Huberregressionisusedtoreducetheweightgiventooutliers inthedata.Youwillneedtospecifytwoadditionalpiecesofdata. Thefirstisthevariableintowhichtheprogramplacestheweights andthesecondisthevalueoftheresidualatwhichtheweights shouldstarttobechanged.Thisprocedurecanreallyonlybeused afterfirstdoingatraditionalregression. Weightedregressionrequiresyoutospecifyaweightvariable beforeexecution. ChowregressionisasimplemodificationofMultiple.Itis usedtoseeiftheregressionparametersareconstantoverthescope ofthedatavariables.Youwillhavetospecifythenumberofpoints tokeepinthefirstsample. PrincipleComponentsisnotactuallyaregressionmethodat all.Itisaprocessusedtoreducethenumberofvariablesneeded toexplainthevariationinthedata.Theresultantvariablesare orthogonal;thatisthecorrelationbetweenany2variablesis0. Regressioncanoftenthenbecarriedoutagainstthesepseudo variables.Theprocessisdestructiveinthatitwipesoutthe existingvariables.Eachnewoneisalinearcombinationofthe others. Correlationmatrix Ratherthanafullregressionyoumaysimplywanttoseethe correlationbetweenagroupofvariables.Thisisoftendonetolook attheeffectsofmulticolinearityonthedata. TimeSeries  Thesearemethodsofsmoothingorprojectingdata.Theyareoften usedincombinationwithotherprocedures. Movingaveragerequiresyoutochoosethevariableandthe periodofthemovingaverage.Aswellyoumustselectavariable intowhichtheaveragedvariablewillbeplaced. Geometricmovingaveragesrequirethesameinputaslinear movingaverages. Fouriersmoothingrequiresavariabletosmoothandavariable toplacetheresult.Italsoasksforthenumberoftermstobekept intheintermediatecalculations.Thisvalueshouldbelessthan50, usuallylesthan15.Theremustbenomissingdataforthis proceduretowork.Notethatthiscanbeaslowprocess. Brown1wayexponentialsmoothing Thisissimpleexponentialsmoothing.Youwillbeaskedto specifythevariabletosmoothandavariabletostoretheresult. Inadditionyouwillneedasmoothingconstant(0to1)anda startingvalue.Ifyoudonotspecifythestartingvaluetheprogram willgenerateone.Thisprocessisnotdesignedfordatawitha distibcttrendline.Ifthereisadistinctlineartrendthen2way exponentialsmoothingshouldbeused. Brown's2wayexponentialsmoothinguseslinearregressionto estimateastartingvalueandtrend.Youmustestimatethesmoothing coefficientandvariabletosmoothandvariableforresult. Holt's2wayexponentialsmoothingissimilartoBrown'sexcept thataseparatesmoothingcoefficientisusedforthetrendfactor. Ifthereisaseasonalaspecttothedata(likeretailsales whichhaveaDecemberpeak)thenWinter'sexponentialsmoothing shouldbeused.Youwillhavetoenter4quantities.Thefirstis thesmoothingcoefficientforlevel.Thesecondisfortrend.The thirdisforseasonality.Thefourthvalueistheperiodof seasonality.Notethatthismethodshouldnotbeusedifthedata fluctuatesaboveandbelowzero.Ifthedatadoesgobelowzeroand youwanttousethismethodaddaconstanttothedatatomakeit allpositive.Thenaftersmoothingsubtracttheconstant. Interpolation B/STATuses3formsofestimatingunavailabledata.Thefirst issimplelinearinterpolation.Forthisyousimplyselectthe variable.ThesecondisLagrangianinterpolation.Forthisyouneed 2variables;an"X"variableanda"Y"variable.Therecanbeno missing"X"variables.Thethirdmethodisthemethodofcubic splines.Thisprocedureassumesthatthedataintheselected variableconsistsofeavenlyspacedobservations.Notethat Langrangianinterpolationcanbeslowifthereisalotofdata sinceeachpointisusedinestimatingmissingdata. Extract Theseselectionsallowyoutoreducetheamountofdatainthe dataset.Thefirstoptionsumsthedata.Forexampleifyouwantto getyearlytotalsfromadatasetofmonthlydatayoucanextract summeddataandreducethedatabyafactorof12.Eachelement wouldthenbeayearlytotal.Inthenonsummedcaseonlyevery12th valuewouldbeleft.Nosummingwouldbedone.Thisisusefullif youwanttolookatsubstesinisolation. Miscellaneous Thismenuhastwoproceduresinadditiontotheusualhelp selection. Crosstabs Thisprocedureisusedtosummarizedatawhichliesin2or threevariables.Itproducesacountforthecombinationofvalues inthechosenvariables.Forexampleyoumayhavedataonthe heightandweightofagroupofarmyrecruits.Youcoulduse crosstabstofindoutthenuberineachheightandweight classificationwherethesecouldbeheightin2inchincrements andweightin5poundincrements.Itismostcommonlyused inmarketresearchforcrossessuchasbetweenage30and34and earningbetween20and30000dollarsperyear. Youfirstselectthevariablestouseinthecrosstab. Ifyouselect2thena2waycrosstabisdone.If3thena3way crosstabisdone.Nextyouselectthebreakpointsfortheclasses ineachvariable.Theremaybe14breakpointsgiving15classes maximumforeach.Youneedonlytypeinasmanybreakpointsas thereareandleavetherestblank.Thenumberofbreakpointscan bedifferentforeachvariable.Notethatthelowerclass includesthebreakpoint.Thusabreakpointof200poundswould put200poundpeopleinthelowerclassand200.01poundpeople inthehigherclass.Theprogramwillprintouttheresults.Ifyou wantyoumayreplacethedatainmemorywiththesummarized totals.Thiscanbequiteusefullifyouthenwanttoperformachi squaretesttype2ontheresulttoseeifthereareany significantrelationships. Difference Thisprocessisquitesimple.Thedifferenceofavariable issimplyitschangefromoneperiodtothenext.Sometimes someprocedureswillworkbetteronthechangeinavariable ratherthanthevariableitself.ThisisespeciallytrueinBox Jenkinsanalysis. Theinputisquitesimple.Youareaskedthevariableto differenceandthevariableintowhichtoplacetheresult. GRAPHICS Graphmenu Theregularselectionwillgraphthedatawiththelabelsyou haveenteredinthedataentryareaalongthe"X"axis.Thetypeof graphwilldependontheselectionsyouhavemadeinthe"styles" area.Upto6variablesmaybechosen.Youmayplotsomeagainstthe leftaxisandsomeagainsttherightaxis.Thehorizontalgraph optionputsthelabelsonthe"Y"axisandthevaluesalongthe"X". Youcannothavearightsideaxisforthistypeofgraph. "XY"graphsallowupto6pairsofvariablestobeused.You mustselectyourdataapairatatime.Thefirstonechosenofeach pairwillbethe"X"valueofthepointandthesecondwillbethe "Y".Youmayrepeatthesameselectionbetweenpairssothatyoucan haveseveralvariablesgraphedagainstthesame"X".TherearenoXY bargraphs.Youcannothavearightsideaxis. HILOgraphsarestockmarketgraphs.Thefirst3variables chosenwillbedisplayedasahighlowclosetypeofgraph.The remainderofthe6possiblegraphswillbeshownasselectedonthe stylessection.Youcanuserightsideaxiswhichallowsyouto graphvolumeonthesamegraphasstockprices.Youcanhaveahi lowgraphwithonly2variables.Inthiscasethedatarepresents simplyahiandlowbutnoclose. Piecharts.Youmayhaveupto4piesonthescreen.Simply specifythecorrectnumberofvariables.Aspecialcaseexistsfor2 piechartsifyouhaveselected"componentpies"fromthefeatures menu.Inthiscasethesecondvariablewillbeassumedtobean explosionofthefirstpiesegment.Bubblegraphsrequire3 variablestobechosen.Thefirstspecifiesthe"X"valueofthe point.Thesecondspecifiesthe"Y"valueofthepointandthethird specifiestherelativeareaofthebubble. OPPOSEDBARSrequire2variableswhichmustbepositive. Iflogsareontheyareignored.Opposedbarsaregoodfor comparingsimilardataagainstoneanother.anexamplemightbe thepopulationoftheU.S.A.byagegroupwhereone variablerepresentsmalesandanotherfemales.Thekeyfeature ofopposedbarsisthatthereisnooffsetbetweenthevariables. Onepeculiarityoftheimplementationcomesupinrescaling. Thesecondvariableistreatedasbeingnegativebythe program.Thustheminimumvalueisshownasanegative.This isarequirementsoensurethatyouenteranegativeforthe minimum,eventhoughitwillbeprintedasapositive. FLOATINGBARSrequire2variablesforeachbarplotted. Thefirstrepresentstheminimumofthefloatingbarandthe secondthetop.LikeXYgraphsyouwillcontinuetobepromptedfor inputuntilyoufailtoenter2variables.ThisisnotanXY graphhowever.TheX-axisisscaledbythelabelsjustasfora regulargraph. HORIZONTALFLOATINGBARSarethesameasregularfloating barsexceptthatthegraphisdonehorizontally. STATGRAF Theseproceduresareparticulargraphtypesusedforanalysis. Astargraphproducesachartdescribingthephysicalvaluesof severalvariablesateachofseveralpoints.Thereshouldbeno negativevalues.Foreachpointaseriesoflinesaredrawnstarting at3O'clockandthenworkingcounterclockwisearoundthepoint. Thelengthofthelinesrepresentshowhighthevalueofthe variableisforthatpoint.Theminimumvalueofthelineissetto 20percentofthemaximum. Asunraygraphissimilarinconcept.Inthiscaseeachline isthesamelengthbutthelineiscutatavalueindicating relativelength.Ifthelineiscutexactlyinthemiddlethenthe pointhasavalueforthatvariablewhichisatthemeanforall points.Aboxwhiskergraphrequirestheselectionofavariableand acategoryvariable.Theboxandwhiskerarethendrawnforvalues fromthefirstvariablewherethecategoricalvariableisata certainlevel.Theboxandwhiskerisaregularstylegraph.Thebox hasit'stopvaluatthe3rdquartilepointanditsbottomatthe firstquartile.Theboxisbisectedbyalineatthemedian. Extendingoutfromtheboxattopandbottomarethewhiskers.These reachouttothehighestandlowestpointinthedatavariablefora givenlevelofthecategoricalvariable. Thenotchedboxwhiskeristhesameexceptthatthereisan additionalpieceofinformationgiven.Thereisanotchinthebox whichcoversa95percentconfidencelimitonthemedian.Thedepth ofthenotchisproportionaltothenumberofelementsinthe variablewiththatvalueofthecategoricalvariable. SETTINGS Thesettingsmenuallowsyoutodefinehowthegraphwilllook. Thepalettesettingallowsyoutosetthepaletteforthegraph. Stlesallowssettingthelinestylefillpatternandpointstyle.It alsoallowsyoutoturnonlinesbarsorpoints.All3canbeonfor anygivenvariable.PieStyleallowsyoutosetcolorsandfill stylesforpiesaswellaswhetherasliceisexploded.Axesallows turningscalingoraxesonandoffaswellasselectingthecolorto beused.Titlesallowsyoutoenterthetitlestobeusedonthe graph.TitleFontsallowsyoutoselectthecolorandstyleofthe maintitleandthesubtitle. Features Boxedmeansthatforregularandhorizontalgraphsalinewill bedrawntocloseinthegraph.Rtsideaxiswillallowarightside axisonregulargraphs. Stackedwillgivestackedbargraphsandareagraphsforline graphs. Filledwillcausetheareabetweenlinestobefilledin.It cannotbecombinedwithstacked. Valsabovewillcausethevalueofthepointtobedisplayed aboveitforregularandhorizontalgraphs.ForPiechartsthe valueswillbeprintedbelowthepielabel. Legendwilcausethelegendforeachvariabletobedisplayed. Ifturnedoffthenthegraphwillbelargerbutyouwillhavetouse customlabellingtodefinewhatthevariablesare.  LogXcausestheXaxistobeonaLOGbasis. LogYdoesthesamefortheYaxis. ProportionalPiemeansthatifmorethan1pieisshownonthe screenatoncethererelativesizeswillbedeterminedbythetotal ofthevaluesineachpie.Thisisquiteusefullwhencomparing4 yearsofsalesdata. ComponentPie.When2variablesareselectedforapiegraph thisoptioncausesthesecondvariabletobetakenasasubsetof thefirstpiesector.Thevaluesinthesecondvariableare displayedasastackedbarsettotherightofthepie. PiePercentwillcausethepercentageeachpieslice representstobeprintedinthepieslice.Thepercentis roundedtothenearestwholepercentage. Grids Thesetwooptionsturnonhorizontalandverticalgrids.There isalsoa"zeroline"optiontoensurethatalineisdrawnatthe zeropointevenifnogridsaredisplayed. Whileagraphisonscreenlabelsmaybeaddedbydouble clickingwhereyouwantthemtoappear.Youwillberequiredto selectthefontandsizeforthelabeljustasfortitles.You havetheoptionofaddinganarrow.Simplyclickwhereyouwantit topoint.Theselabelsmaybedraggedonthescreen.To removeafloatinglabel,doubleclickonthelabel.Youarenow asked"WhattoChange?".Thiscanbeeitherfont,text,or arrow.Youcanremovethelabelbyselectingtextanderasingthe existingtext.alabelwithnotextissimplyremovedfrom thelistoflabels.Ifyouchoosearrowyoucaneitheraddan arrowifonedoesnotexistormovetheanchorpointforan existingarrow,orremovethearrow. Themenubardisplayedwhileagraphisonscreenallowsyou tosaveorprintthegraph.Selecting"SAVE"willcreateaDegas uncompressedimageonyourdisk.Whenprintingyouhavethree options.FirstyoucanprintthescreenusingthebuiltinAtari screendumputilityoronewhichyouhaveloadedyourself.The secondoptionisusefullonlyfor9pinEpsonprinters.This optionusestheEpsonplottermodetoensureproperlyscaled pictures.Italsoonlyworkswiththemonochromemonitor.Thelast choiceusesGDOSifyouhaveittoplottotheprinter.Thetexton thegraphwillnotusuallylookquitethesameasonthescreen sincemanyGDOSfontsareproportionalandthedefaultscreen fontsarenot.Alsosomeoftheprinterfontsarenotquitethe samesizeasthescreenfonts. Alsoonthisscreenyoucanrescalethegraph.Selections existforrescalingtheX-axis,oreitherY-axis.Youmust inputthemaximum,minimum,distancebetweenlabelsanddistance betweentics.Themiscellaneousmenuallowsyoutoreturneither tothetopmenuortothegraphselectionmenu.Another selectionallowsyoutochoosewhetheryouwantfloatinglabels erasedonexitormaintained.  Critical Values of Wilcoxon Statistic One Tail Test No of Significance Level Points 5% 1% 6 2 NA 7 4 0 8 6 2 9 8 3 10 11 5 11 14 7 12 17 10 13 21 13 14 26 16 Critical Values of Wilcoxon Statistic One Tail Test No of Significance Level Points 5% 1% 15 30 20 16 36 24 17 41 28 18 47 33 19 54 38 20 60 43 21 68 49 22 75 56 23 83 62 Critical Values of Wilcoxon Statistic One Tail Test No of Significance Level Points 5% 1% 24 92 69 25 101 77 06300030201800 1 2# 6L....T....T....T....T....T....T....T....T....T....T....T....T....R Themainmenuareaisusedfortravellingbetweenmenusandfor loadingandcreatingfiles.Creatingfilesfirstrequests informationonthetypeoflabeltobeusedforthedata.These labelsareonlyusedforgraphing.Theydonothaveanyimpacton thestatisticalproceduresintheprogram.Theymaybeinitialized asblanks,tobefilledinlaterbyyou.Theymaysimplybea counterinwhichcaseyouwillbeaskedtospecifythestarting valueandarateofincrement.Thisoptionwouldbeusedifyou wantedtospecifycalendaryearssuchas1988.Youmayselectmonths asalabel.Inthiscaseyoumustenteranumericvalueforthe monthsuchas1forJanuaryetc.Thedatamaybespecifiedasdays oftheweekorweekdays.Thedifferencebetweenthese2isthatdays oftheweekincludesSaturdayandSunday,whileweekdaysincludes onlyMondaytoFriday.Foreachoftheseoptionsyouhave13 differentwaysinwhichthedatemaybeshown.Thesearedisplayed inagridof27squaresonthescreen.Clickingthemousebuttonon oneofthesquareswillhilightthestyle.asubsequentclickwill returnthesquaretonormal.ClickingonEXITwillmakethechoice official.ThisstyleofdialogboxisusedthroughoutB/STATfor selectingvariables. Afterselectingthestyleyoumustspecifythedateinformation aboutthestartingdayforthedata.Thesevaluesmustbespecified numerically.TheweekisassumedtostartonMondayso1isMonday and7isSunday.Ifyouenteranimpossiblemonthsuchasmonth23 theprogramwilltakethemodulusof12andthisnumbertogenerate thestartingmonth.Similaractionsoccurforthedayandthedayof theweek.Yearsmaybeenteredas1988orassimply88.Anynumber below100istreatedas1900+thenumber;anynegativenumbersare convertedtopositivessounfortunatelyyearssuchas34BCwillhave tobetypedasmanuallabels. Oncethetypeoflabelisenteredyouwillmovetothe spreadsheetstyledataentryscreen.Thisscreenallowsfor26 columnsofdataandasmanyrowsasyouinitializedintheprogram. Theminimumnumberofdatarowsis19.B/STATisnotaspreadsheet. Thisscreenissimplyfordataentryalthoughsomefacilityfor variablecreationdoesexist.Thespreadsheetusesbothmenudrop downsandcommandsforoperation.Forrapidmovementaroundthe spreadsheetthe">"commandisused.>s45willmovethecursorto column"S"androw45automatically.Aswelltherearecommandsfor sortingcolumns,addingthemtogetheretc.Thecommandlistis availablebyselectingthehelpmenufromthedataentryscreen.For missingdataenterNAasthevalue. Thenormalviewofthecolumnsinthespreadsheetisas separatedatavariables.Therearestatisticalprocedureshoweverin B/STATwhichtreattheentirecollectionofdataasamatrixof data.Theseproceduresarediscussedmorefullyinthemanualandin theindividualhelpscreens. B/STATallowsforsavingandloadingdifferentdataformats. StraightsaveandloaddosoinB/STAT'sformat.DIFloadandsave dosointhedatainterchangeformatintroducedbyVISICALCmany yearsagoandcurrentlysupportedbymostprograms. B/STATwillaskyouifyouwanttoloadthedatabycolumnor row.Strictlyspeakingthequestionismisleading.Intheoriginal DIFstandardyoucouldsavethedatabyroworbycolumn.Many programstodaygiveyounosuchchoicesoyoucannottellwhether thevariablesweresavedasrowsorcolumns.Similarilyneithercan B/STAT.Itcannotknowwhetherthedatarepresents12variables with20pointseachor20variableswith12pointseach.Wesuggest thatyoutryloadingdatabycolumnandthencheckingtoseeifit cameinproperly.Ifnotthenreloadbyrow.Fromthenonyouwill knowthatdatafromthatprogrammustbeloadedintoB/STATinthat fashion.NotethatB/STATcanacceptonlynumericdatainaDIF file. AnASCIIfilereferstoafilewhereeachrecordisanumber. TobeusedbyB/STATthedatamustbeinthefollowingorder #rowsused #columnsused datavalueforcol1row1 datavalueforcol2row1 datavalueforcol3row1 etc PRNfilesarecreatedbymanyspreadsheetprograms.Theseare actualdiskimagesofpageswhichwouldotherwisehavebeenprinted. OnlynumericsareallowedinB/STAT.Thedatamusthavebeensaved insuchawaythatthecolumnsrepresentdatavariables. Editingafilesimplyplacesyouinthespreadsheetdataeditor withoutdestroyingtheexistingdata.Thisalowsforaddingor changingdata. Thehelpdriveselectionallowsyoutochangethedrivepath forfindingthehelpfiles.Uponstartingtheprogramthedrive searchedforthefilesistheonefromwhichtheprogramwas started. The"Tables"selectionsloadinstandardstatisticstablesso thatyoucancheckvaluesagainstthem.Notallpossibletablesare present.TablesarenotusedfortestswhereB/STATisableto calculatetheprobabilitybydirectmathematicalmeans. Thedataeditorisdesignedforefficiententryofdatafor furtheranalysis. Dataisassumedtobeintheformofvariableswhicheach occupyacolumn. Variousoperationscanbeperformedonthevariablesby enteringcommandsonthecommandline. Thefirstgroupaffectthevariableinwhichthecursorislocated. AssumethatvariableYcontainsthecursor.Theoperationsare: a+bVariableYisthesumofvariablesaandb a+xVariableYisthesumofvariableaandconstantx a-b a-x a/bVariableYequalsvariableadividedbyvariableb a/xa*bVariableYequalsvariableatimesvariableb a*x a^bVariableYequalsvariableatothepowerofvariableb a^xVariableYequalsatopowerofconstantx abVariableYis1ifagreaterthanbelse0 a>xVariableYis1ifagreaterthanconstantx a\bVariableYisminimumofaandb a\xVariableYisminimumofaandconstantx a|bVariableYismaxofaandb a|xVariableYismaxofaandconstantx a!bSwapsvariablesaandb.Yisnotaltered a!xSetsvariableatovaluex a@xVariableYisaccumulationofaatx%interest paymentsatendofperiod a&xVariableYisaccumulationofaatx%interest paymentsatstartofperiod a@bVariableYisaccumulationofaatinterestratesgiven incolumnb a&bsameasa@bbutpaymentsatstart a$xVariableYispresentvalueofpaymentsat interestratex%paymentsatendofperiod a$bsameexceptvaryinginterestgiveninb a#xAsfora$xexceptpaymentsatstart a#bAsfora$bexceptpaymentsatstart a%xfindsinternalrateofreturnsuchthatPV ofcolumnaequalsxpaymentsatendofperiod a%bFindsaseriesofyieldratessuchthatthePV ofcolumnaequalsthevalueincolumnb TheresultsgoinY RADTODEG(a)VariableYisconversionofatodegrees degtorad(a)VariableYisconversionofatoradians sort(a)sortsvariableainascendingorderYunused sortall(a,b,c)sortswholedatasetwithkeysa,b,c notallkeysneededbutatleast1 counterxxVariableYisfilledwithacounterfrom1to xx blankVariableYisblankedout mult(a)VariableYisrunningproductofa rot(a)VariableYisrotateda fact(a)variableYisfactorialofa abs(a)VariableYisabsolutevalueofa sqr(a)VariableYissquarerootofa sin(a)VariableYissinofa cos(a)VariableYiscosofa tan(a)VariableYistanofa asin(a)VariableYisarcsinofa asec(a)VariableYisarcsecantofa acos(a)VariableYisarccosofa atn(a)VariableYisarctanofa log(a)VariableYislogofa exp(a)VariableYisetothepowerofa log10(a)VariableYislogtobase10ofa exp10(a)VariableYis10tothepowerofa int(a)VariableYisintegerpartofa asinh(a)VariableYisarchyperbolicsinofa acosh(a)VariableYisarchyperboliccosofa atanh(a)VariableYisarchyperbolictanofa sinh(a)VariableYishyperbolicsinofa cosh(a)VariableYishyperboliccosofa tanh(a)VariableYishyperbolictanofa amort(amount,term,conv,payts,intr) amortizesaloanofamount"amount"over aperiodof"term"years. interestisconvertible"conv"timesperyear thereare"payts"paymentsperyear(iemonthlyis12) theinterestrateisspecifiedinpercentby"intr" >axx Thiscommandcausesthecursortogotocolumn"a"row"xx" Cursormovementscanbemadeusingthearrowkeys.Holdingdownthe "Control"keyandpressingthearrowkeyscausesmovementofafull page. STATS1Menu NormalityTests These2testcheckwhetheravariableisdrawnfromanormal population.Inbothcasesyoumustselectthevariabletooperate on.Inthecasewhereyouknowtheparametersyouwillbeaskedfor themeanandstandarddeviationoftheunderlyingpopulation.The programwillnotevaluatethestatisticreturned.Publishedtables mustbeused DescriptiveStatistics Thesetestsprovidemean,standarddeviation,kurtosisetcfor thedataset.Ifthedataisgroupedyouwillhavetoselecta groupingvariableaswellasthedatavariable. Correlation Theseprovidesimplecorrelationtests.Simplecorrelationis thecorrelationbetween2variableswhichyouchoose.TheSpearman rankcorrelationtestcomparestheranksof2setsofvariables ratherthantheactualnumbers.Thecontingencycoefficienttest compares2variablesonaparametricbasis.Datamustbenon negativeandscalednominally KendalConcordanceisusedwith3ormorevariableswhichareinthe formofranks.Noselectionofvariablesismade.Theentiresetof datainmemoryisused. TheKendalTautestissimilartotheSpearmanranktest.Itisused for2variablesintheformofranks. ThePointBiserialcorrelationtestisusedwith2related variables.Onevariablerepresentstheresultandtheotherthe classificationbasedonadichotomousvariable.Adichotomous variableisonewhichcanhaveonly2values0or1.Forexample maleversusfemale.Youwillbeaskedseparatelyforthe2 variables. LaggedAutocorrelationdeterminesthecorrelationofa variablewithitselfatanearliertime.Theprogramwillaskfor thevariabletobeexaminedandavariableintowhichtostorethe results.Theresultisaseriesofvaluesspecifyingthecorrelation foramultitudeoflagperiods.Thefirstvalueiswith0lagand hasvalue1. LaggedMultipleCorrelationissimilartotheaboveexceptthat 2variablesareexamined.Inthiscaseyouareaskedfor2 variables.Orderofselectionisimportant.Thelagperiodwill refertothevalueofthesecondvariable"K"periodsearlier.Thus ifVariable"A"istoberelatedtoVariable"B"atearlierperiods, youshouldselectVariable"A"firstand"B"second. OrdinalTests KolmogorovSmirnov Checksasinglevariabletodetermineifthevaluessupportthe hypothesisthatthedifferencesbetweenthemarechance. MannWhitney Requires2independentsamples(variables).Thevariablesdo nothavetobethesamesize.Thedatarepresentsaranking.Thetest determineswhetherthereappearstobeadifferencebetweenthe samples.Smallvaluesareextremeforthistestsothecomparison is"isthevaluelessthanthetablevalue?" Wilcoxontest SimilartotheMannWhitneyexceptthatthesamplesare related.LiketheMannWhitney,smallvaluesareextreme.Thusif thecalculatedvalueislessthanthetabularvalueyourejectthe nullhypothesisthatthereisnodifferencebetweensamples. KruskalWallistest Forthistestalldatainthedatasetisused.Theremustbe atleast3variables.Thetestisbasicallythe3ormorefactor equivalenttoMannWhitney.Theextremevaluesarehighunlike theMannWhitney. Friedmantest Alldataisused.Thisisthe3ormorefactorequivalentto theWilcoxontest.Howeverbecauseoftheformulationofthe statisticextremevaluesarehigh. Mediantest 2variablesareselected.Thetestindicateswhetherthe2 samplesappeartobedrawnfrompopulationswiththesamemedian. Runstest Thistestisusedfor1variable.Inadditionyoumustchoose whetherthetestcriteriaiszero,themeanorthemedian.Thetest determineswhetherthedataappearstoberandomlydistributedabout thecriteria. Signtest Youmustchooseavariableandthenatestvalueforthe median.Theprogramcalculatesaprobabilitythatthechosenvalue isindeedthemedianofthepopulationfromwhichthedatais selected. NominalTests ChiSquare1 2Variablesareusedwiththefirstrepresentingtheexpected andthesecondtheactual.Thetestdetermineswhethertheactual dataisconsistantwiththeexpected ChiSquare2 Thistestusesallofthedata.Thedataisassumedtobeset upinacontingencymatrixform.Thenullhypothesisisthatthere isnorelationshipbetweentherowsandcolumns. McNemartest Alldataisused.Theremustbe2rowsand2columns.Itisa testusedtoinvestigatechangesinresponseinapreandpost stimulousstudy.Seethemanualfordatasetup. Cochrantest Alldatainthedatasetisused.Theremustbe3ormore relatedvariables.Thedataisdichotomousinnature.InB/STAT positivesaretreatedas1negativesor0as0.Thetestusesthe nullhypothesisthatthereisnodifferencebetweenvariables.STATS 2MENUITEMS Distributions Thissetofitemscalculatesprobabilitiesforthegiven distributionbaseduponvalueswhichyouinputinresponseto questions.Nodatavariablesareused. TTests Thereare3T-testsavailable.Test1calculatesthechancethat agivenvariablehasacertainmean.Youareaskedtochoosea variableandtospecifyameantotest.Thesecondtestchecksthe chancethat2variableshavethesamemean.Youhavetoselect2 variables.The2variablesshouldberandomlyselectedand unrelated.ThethirdTtestisdesignedfor2variableswhichare related.Onceagainyousimplyselect2variables. Multivariate Thereare2proceduresFactoranalysisand Discriminantanalysis.Thesearesomewhatsimilar.Forfactor analysisyoufirstselectthevariableswhichyouwantinthestudy. Youmustthenselectthetypeofrotationdesired.Ifyouchoosean orthobliquerotationthenanorthobliquefactormustbeentered.The orthobliquefactormustbefrom0to.5 Indiscriminantanalysisyoumustfirstselecttheindependant variables.Younextchoosethedependantvariable. Inbothproceduresthedataentryscreenisusedtodisplay results.Notextinputcanbemadebutallmenufunctionsandarrows work. ANOVA TheAnalysisofVariancesectionallowsforflexibilityindata structure.Theonewaystudiesallrequirethatthedatabesetup inatraditionalANOVAmatrixstructure.Questionswillnotbeasked fortherandom,blockedorlatinsquaredesigns.Fornestedyou willbeaskedtospecifythenumberoftreatmentsinablock. Forthe2and3wayANOVAdesignsthedatacanbeeithersetup inamatrix(thedefault)orseparatevariablescanbeusedto representthelevelsofthevariables.Ina3waydesignnotusing matricesyouwouldbeaskedforthevariablethatheldtheresults andtheninturnforthevariablecontainingthelevelinformation forfactorsABandC.Ifthedatawasinmatrixformyouwouldneed tospecifythenumberoflevelsinAandB. Forthe2factorcasetheinputrequiredissimilar. VarianceTests Theonefactortestasksforavariablenameandavalueto test.Thevaluetestedisthestandarddeviationandtheprogram willgivebackthechanceofthevariablewaschosenfroma populationwiththegivenstandarddeviation.The2factortest compares2variablestodeterminethechancethattheyareboth drawnfromapopulationwiththesamestandarddeviation.  STATS3MENU Regression Thefirst7itemsallhavesimilarinputandoutputstructures. Youwillbeaskedforthevariableswhicharetheindependent variablesandforthe1dependentvariable.Youwillthenbeasked forthevariableintowhichthecalculatedvaluesshouldbeplaced. Theprogramdoesnotplacetheresidualsinavariableaasthiswould restrictthenumberofvariableswhichcouldactuallybeusedinthe regression.Togettheresidualssimplysubtractthecalculateddata fromtheactualinthedataeditor.Thedifferencesliein additionalpartsoftheregressions.TheMultipleregression selectionisatraditionalregression.Ridgeregressionwillrequire theentryofaridgefactorwhichshouldbesmallandbetween0and 1(mostoftenbelow.2) StepwiseregressionislikeMultiple,exceptthatyouspecify allindependentvariablestobeconsidered.Theprogramdecideson whichofthesetoactuallyuseintheregression. CochranreferstoaregressiondoneusingtheCochran-Orcutt procedure.A"Cochran"factorofbetween0and1mustbeused.This typeofregressionactuallyusesapartofthepreviouspointinthe calculation.IftheCochranfactoris1thentheregressionis actuallycalculateduponthefirstdifferencesofthevariables. Huberregressionisusedtoreducetheweightgiventooutliers inthedata.Youwillneedtospecifytwoadditionalpiecesofdata. Thefirstisthevariableintowhichtheprogramplacestheweights andthesecondisthevalueoftheresidualatwhichtheweights shouldstarttobechanged.Thisprocedurecanreallyonlybeused afterfirstdoingatraditionalregression. Weightedregressionrequiresyoutospecifyaweightvariable beforeexecution. ChowregressionisasimplemodificationofMultiple.Itis usedtoseeiftheregressionparametersareconstantoverthescope ofthedatavariables.Youwillhavetospecifythenumberofpoints tokeepinthefirstsample. PrincipleComponentsisnotactuallyaregressionmethodat all.Itisaprocessusedtoreducethenumberofvariablesneeded toexplainthevariationinthedata.Theresultantvariablesare orthogonal;thatisthecorrelationbetweenany2variablesis0. Regressioncanoftenthenbecarriedoutagainstthesepseudo variables.Theprocessisdestructiveinthatitwipesoutthe existingvariables.Eachnewoneisalinearcombinationofthe others. Correlationmatrix Ratherthanafullregressionyoumaysimplywanttoseethe correlationbetweenagroupofvariables.Thisisoftendonetolook attheeffectsofmulticolinearityonthedata. TimeSeries  Thesearemethodsofsmoothingorprojectingdata.Theyareoften usedincombinationwithotherprocedures. Movingaveragerequiresyoutochoosethevariableandthe periodofthemovingaverage.Aswellyoumustselectavariable intowhichtheaveragedvariablewillbeplaced. Geometricmovingaveragesrequirethesameinputaslinear movingaverages. Fouriersmoothingrequiresavariabletosmoothandavariable toplacetheresult.Italsoasksforthenumberoftermstobekept intheintermediatecalculations.Thisvalueshouldbelessthan50, usuallylesthan15.Theremustbenomissingdataforthis proceduretowork.Notethatthiscanbeaslowprocess. Brown1wayexponentialsmoothing Thisissimpleexponentialsmoothing.Youwillbeaskedto specifythevariabletosmoothandavariabletostoretheresult. Inadditionyouwillneedasmoothingconstant(0to1)anda startingvalue.Ifyoudonotspecifythestartingvaluetheprogram willgenerateone.Thisprocessisnotdesignedfordatawitha distibcttrendline.Ifthereisadistinctlineartrendthen2way exponentialsmoothingshouldbeused. Brown's2wayexponentialsmoothinguseslinearregressionto estimateastartingvalueandtrend.Youmustestimatethesmoothing coefficientandvariabletosmoothandvariableforresult. Holt's2wayexponentialsmoothingissimilartoBrown'sexcept thataseparatesmoothingcoefficientisusedforthetrendfactor. Ifthereisaseasonalaspecttothedata(likeretailsales whichhaveaDecemberpeak)thenWinter'sexponentialsmoothing shouldbeused.Youwillhavetoenter4quantities.Thefirstis thesmoothingcoe======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ======== SORRY, THIS SECTOR CANNOT BE READ FROM FLOPPY DISK BY ST RECOVER. ======== ==mplyselectthe variable.ThesecondisLagrangianinterpolation.Forthisyouneed 2variables;an"X"variableanda"Y"variable.Therecanbeno missing"X"variables.Thethirdmethodisthemethodofcubic splines.Thisprocedureassumesthatthedataintheselected variableconsistsofeavenlyspacedobservations.Notethat Langrangianinterpolationcanbeslowifthereisalotofdata sinceeachpointisusedinestimatingmissingdata. Extract Theseselectionsallowyoutoreducetheamountofdatainthe dataset.Thefirstoptionsumsthedata.Forexampleifyouwantto getyearlytotalsfromadatasetofmonthlydatayoucanextract summeddataandreducethedatabyafactorof12.Eachelement wouldthenbeayearlytotal.Inthenonsummedcaseonlyevery12th valuewouldbeleft.Nosummingwouldbedone.Thisisusefullif youwanttolookatsubstesinisolation. Miscellaneous Thismenuhastwoproceduresinadditiontotheusualhelp selection. Crosstabs Thisprocedureisusedtosummarizedatawhichliesin2or threevariables.Itproducesacountforthecombinationofvalues inthechosenvariables.Forexampleyoumayhavedataonthe heightandweightofagroupofarmyrecruits.Youcoulduse crosstabstofindoutthenuberineachheightandweight classificationwherethesecouldbeheightin2inchincrements andweightin5poundincrements.Itismostcommonlyused inmarketresearchforcrossessuchasbetweenage30and34and earningbetween20and30000dollarsperyear. Youfirstselectthevariablestouseinthecrosstab. Ifyouselect2thena2waycrosstabisdone.If3thena3way crosstabisdone.Nextyouselectthebreakpointsfortheclasses ineachvariable.Theremaybe14breakpointsgiving15classes maximumforeach.Youneedonlytypeinasmanybreakpointsas thereareandleavetherestblank.Thenumberofbreakpointscan bedifferentforeachvariable.Notethatthelowerclass includesthebreakpoint.Thusabreakpointof200poundswould put200poundpeopleinthelowerclassand200.01poundpeople inthehigherclass.Theprogramwillprintouttheresults.Ifyou wantyoumayreplacethedatainmemorywiththesummarized totals.Thiscanbequiteusefullifyouthenwanttoperformachi squaretesttype2ontheresulttoseeifthereareany significantrelationships. Difference Thisprocessisquitesimple.Thedifferenceofavariable issimplyitschangefromoneperiodtothenext.Sometimes someprocedureswillworkbetteronthechangeinavariable ratherthanthevariableitself.ThisisespeciallytrueinBox Jenkinsanalysis. Theinputisquitesimple.Youareaskedthevariableto differenceandthevariableintowhichtoplacetheresult. GRAPHICS Graphmenu Theregularselectionwillgraphthedatawiththelabelsyou haveenteredinthedataentryareaalongthe"X"axis.Thetypeof graphwilldependontheselectionsyouhavemadeinthe"styles" area.Upto6variablesmaybechosen.Youmayplotsomeagainstthe leftaxisandsomeagainsttherightaxis.Thehorizontalgraph optionputsthelabelsonthe"Y"axisandthevaluesalongthe"X". Youcannothavearightsideaxisforthistypeofgraph. "XY"graphsallowupto6pairsofvariablestobeused.You mustselectyourdataapairatatime.Thefirstonechosenofeach pairwillbethe"X"valueofthepointandthesecondwillbethe "Y".Youmayrepeatthesameselectionbetweenpairssothatyoucan haveseveralvariablesgraphedagainstthesame"X".TherearenoXY bargraphs.Youcannothavearightsideaxis. HILOgraphsarestockmarketgraphs.Thefirst3variables chosenwillbedisplayedasahighlowclosetypeofgraph.The remainderofthe6possiblegraphswillbeshownasselectedonthe stylessection.Youcanuserightsideaxiswhichallowsyouto graphvolumeonthesamegraphasstockprices.Youcanhaveahi lowgraphwithonly2variables.Inthiscasethedatarepresents simplyahiandlowbutnoclose. Piecharts.Youmayhaveupto4piesonthescreen.Simply specifythecorrectnumberofvariables.Aspecialcaseexistsfor2 piechartsifyouhaveselected"componentpies"fromthefeatures menu.Inthiscasethesecondvariablewillbeassumedtobean explosionofthefirstpiesegment.Bubblegraphsrequire3 variablestobechosen.Thefirstspecifiesthe"X"valueofthe point.Thesecondspecifiesthe"Y"valueofthepointandthethird specifiestherelativeareaofthebubble. OPPOSEDBARSrequire2variableswhichmustbepositive. Iflogsareontheyareignored.Opposedbarsaregoodfor comparingsimilardataagainstoneanother.anexamplemightbe thepopulationoftheU.S.A.byagegroupwhereone variablerepresentsmalesandanotherfemales.Thekeyfeature ofopposedbarsisthatthereisnooffsetbetweenthevariables. Onepeculiarityoftheimplementationcomesupinrescaling. Thesecondvariableistreatedasbeingnegativebythe program.Thustheminimumvalueisshownasanegative.This isarequirementsoensurethatyouenteranegativeforthe minimum,eventhoughitwillbeprintedasapositive. FLOATINGBARSrequire2variablesforeachbarplotted. Thefirstrepresentstheminimumofthefloatingbarandthe secondthetop.LikeXYgraphsyouwillcontinuetobepromptedfor inputuntilyoufailtoenter2variables.ThisisnotanXY graphhowever.TheX-axisisscaledbythelabelsjustasfora regulargraph. HORIZONTALFLOATINGBARSarethesameasregularfloating barsexceptthatthegraphisdonehorizontally. STATGRAF Theseproceduresareparticulargraphtypesusedforanalysis. Astargraphproducesachartdescribingthephysicalvaluesof severalvariablesateachofseveralpoints.Thereshouldbeno negativevalues.Foreachpointaseriesoflinesaredrawnstarting at3O'clockandthenworkingcounterclockwisearoundthepoint. Thelengthofthelinesrepresentshowhighthevalueofthe variableisforthatpoint.Theminimumvalueofthelineissetto 20percentofthemaximum. Asunraygraphissimilarinconcept.Inthiscaseeachline isthesamelengthbutthelineiscutatavalueindicating relativelength.Ifthelineiscutexactlyinthemiddlethenthe pointhasavalueforthatvariablewhichisatthemeanforall points.Aboxwhiskergraphrequirestheselectionofavariableand acategoryvariable.Theboxandwhiskerarethendrawnforvalues fromthefirstvariablewherethecategoricalvariableisata certainlevel.Theboxandwhiskerisaregularstylegraph.Thebox hasit'stopvaluatthe3rdquartilepointanditsbottomatthe firstquartile.Theboxisbisectedbyalineatthemedian. Extendingoutfromtheboxattopandbottomarethewhiskers.These reachouttothehighestandlowestpointinthedatavariablefora givenlevelofthecategoricalvariable. Thenotchedboxwhiskeristhesameexceptthatthereisan additionalpieceofinformationgiven.Thereisanotchinthebox whichcoversa95percentconfidencelimitonthemedian.Thedepth ofthenotchisproportionaltothenumberofelementsinthe variablewiththatvalueofthecategoricalvariable. SETTINGS Thesettingsmenuallowsyoutodefinehowthegraphwilllook. Thepalettesettingallowsyoutosetthepaletteforthegraph. Stlesallowssettingthelinestylefillpatternandpointstyle.It alsoallowsyoutoturnonlinesbarsorpoints.All3canbeonfor anygivenvariable.PieStyleallowsyoutosetcolorsandfill stylesforpiesaswellaswhetherasliceisexploded.Axesallows turningscalingoraxesonandoffaswellasselectingthecolorto beused.Titlesallowsyoutoenterthetitlestobeusedonthe graph.TitleFontsallowsyoutoselectthecolorandstyleofthe maintitleandthesubtitle. Features Boxedmeansthatforregularandhorizontalgraphsalinewill bedrawntocloseinthegraph.Rtsideaxiswillallowarightside axisonregulargraphs. Stackedwillgivestackedbargraphsandareagraphsforline graphs. Filledwillcausetheareabetweenlinestobefilledin.It cannotbecombinedwithstacked. Valsabovewillcausethevalueofthepointtobedisplayed aboveitforregularandhorizontalgraphs.ForPiechartsthe valueswillbeprintedbelowthepielabel. Legendwilcausethelegendforeachvariabletobedisplayed. Ifturnedoffthenthegraphwillbelargerbutyouwillhavetouse customlabellingtodefinewhatthevariablesare.  LogXcausestheXaxistobeonaLOGbasis. LogYdoesthesamefortheYaxis. ProportionalPiemeansthatifmorethan1pieisshownonthe screenatoncethererelativesizeswillbedeterminedbythetotal ofthevaluesineachpie.Thisisquiteusefullwhencomparing4 yearsofsalesdata. ComponentPie.When2variablesareselectedforapiegraph thisoptioncausesthesecondvariabletobetakenasasubsetof thefirstpiesector.Thevaluesinthesecondvariableare displayedasastackedbarsettotherightofthepie. PiePercentwillcausethepercentageeachpieslice representstobeprintedinthepieslice.Thepercentis roundedtothenearestwholepercentage. Grids Thesetwooptionsturnonhorizontalandverticalgrids.There isalsoa"zeroline"optiontoensurethatalineisdrawnatthe zeropointevenifnogridsaredisplayed. Whileagraphisonscreenlabelsmaybeaddedbydouble clickingwhereyouwantthemtoappear.Youwillberequiredto selectthefontandsizeforthelabeljustasfortitles.You havetheoptionofaddinganarrow.Simplyclickwhereyouwantit topoint.Theselabelsmaybedraggedonthescreen.To removeafloatinglabel,doubleclickonthelabel.Youarenow asked"WhattoChange?".Thiscanbeeitherfont,text,or arrow.Youcanremovethelabelbyselectingtextanderasingthe existingtext.alabelwithnotextissimplyremovedfrom thelistoflabels.Ifyouchoosearrowyoucaneitheraddan arrowifonedoesnotexistormovetheanchorpointforan existingarrow,orremovethearrow. Themenubardisplayedwhileagraphisonscreenallowsyou tosaveorprintthegraph.Selecting"SAVE"willcreateaDegas uncompressedimageonyourdisk.Whenprintingyouhavethree options.FirstyoucanprintthescreenusingthebuiltinAtari screendumputilityoronewhichyouhaveloadedyourself.The secondoptionisusefullonlyfor9pinEpsonprinters.This optionusestheEpsonplottermodetoensureproperlyscaled pictures.Italsoonlyworkswiththemonochromemonitor.Thelast choiceusesGDOSifyouhaveittoplottotheprinter.Thetexton thegraphwillnotusuallylookquitethesameasonthescreen sincemanyGDOSfontsareproportionalandthedefaultscreen fontsarenot.Alsosomeoftheprinterfontsarenotquitethe samesizeasthescreenfonts. Alsoonthisscreenyoucanrescalethegraph.Selections existforrescalingtheX-axis,oreitherY-axis.Youmust inputthemaximum,minimum,distancebetweenlabelsanddistance betweentics.Themiscellaneousmenuallowsyoutoreturneither tothetopmenuortothegraphselectionmenu.Another selectionallowsyoutochoosewhetheryouwantfloatinglabels erasedonexitormaintained.  07000030201800 1 2# 6L....T....T....T....T....T....T....T....T....T....T....T....T....R Themainmenuareaisusedfortravellingbetweenmenusandfor loadingandcreatingfiles.Creatingfilesfirstrequests informationonthetypeoflabeltobeusedforthedata.These labelsareonlyusedforgraphing.Theydonothaveanyimpacton thestatisticalproceduresintheprogram.Theymaybeinitialized asblanks,tobefilledinlaterbyyou.Theymaysimplybea counterinwhichcaseyouwillbeaskedtospecifythestarting valueandarateofincrement.Thisoptionwouldbeusedifyou wantedtospecifycalendaryearssuchas1988.Youmayselectmonths asalabel.Inthiscaseyoumustenteranumericvalueforthe monthsuchas1forJanuaryetc.Thedatamaybespecifiedasdays oftheweekorweekdays.Thedifferencebetweenthese2isthatdays oftheweekincludesSaturdayandSunday,whileweekdaysincludes onlyMondaytoFriday.Foreachoftheseoptionsyouhave13 differentwaysinwhichthedatemaybeshown.Thesearedisplayed inagridof27squaresonthescreen.Clickingthemousebuttonon oneofthesquareswillhilightthestyle.asubsequentclickwill returnthesquaretonormal.ClickingonEXITwillmakethechoice official.ThisstyleofdialogboxisusedthroughoutB/STATfor selectingvariables. Afterselectingthestyleyoumustspecifythedateinformation aboutthestartingdayforthedata.Thesevaluesmustbespecified numerically.TheweekisassumedtostartonMondayso1isMonday and7isSunday.Ifyouenteranimpossiblemonthsuchasmonth23 theprogramwilltakethemodulusof12andthisnumbertogenerate thestartingmonth.Similaractionsoccurforthedayandthedayof theweek.Yearsmaybeenteredas1988orassimply88.Anynumber below100istreatedas1900+thenumber;anynegativenumbersare convertedtopositivessounfortunatelyyearssuchas34BCwillhave tobetypedasmanuallabels. Oncethetypeoflabelisenteredyouwillmovetothe spreadsheetstyledataentryscreen.Thisscreenallowsfor26 columnsofdataandasmanyrowsasyouinitializedintheprogram. Theminimumnumberofdatarowsis19.B/STATisnotaspreadsheet. Thisscreenissimplyfordataentryalthoughsomefacilityfor variablecreationdoesexist.Thespreadsheetusesbothmenudrop downsandcommandsforoperation.Forrapidmovementaroundthe spreadsheetthe">"commandisused.>s45willmovethecursorto column"S"androw45automatically.Aswelltherearecommandsfor sortingcolumns,addingthemtogetheretc.Thecommandlistis availablebyselectingthehelpmenufromthedataentryscreen.For missingdataenterNAasthevalue. Thenormalviewofthecolumnsinthespreadsheetisas separatedatavariables.Therearestatisticalprocedureshoweverin B/STATwhichtreattheentirecollectionofdataasamatrixof data.Theseproceduresarediscussedmorefullyinthemanualandin theindividualhelpscreens. B/STATallowsforsavingandloadingdifferentdataformats. StraightsaveandloaddosoinB/STAT'sformat.DIFloadandsave dosointhedatainterchangeformatintroducedbyVISICALCmany yearsagoandcurrentlysupportedbymostprograms. B/STATwillaskyouifyouwanttoloadthedatabycolumnor row.Strictlyspeakingthequestionismisleading.Intheoriginal DIFstandardyoucouldsavethedatabyroworbycolumn.Many programstodaygiveyounosuchchoicesoyoucannottellwhether thevariablesweresavedasrowsorcolumns.Similarilyneithercan B/STAT.Itcannotknowwhetherthedatarepresents12variables with20pointseachor20variableswith12pointseach.Wesuggest thatyoutryloadingdatabycolumnandthencheckingtoseeifit cameinproperly.Ifnotthenreloadbyrow.Fromthenonyouwill knowthatdatafromthatprogrammustbeloadedintoB/STATinthat fashion.NotethatB/STATcanacceptonlynumericdatainaDIF file. AnASCIIfilereferstoafilewhereeachrecordisanumber. TobeusedbyB/STATthedatamustbeinthefollowingorder #rowsused #columnsused datavalueforcol1row1 datavalueforcol2row1 datavalueforcol3row1 etc PRNfilesarecreatedbymanyspreadsheetprograms.Theseare actualdiskimagesofpageswhichwouldotherwisehavebeenprinted. OnlynumericsareallowedinB/STAT.Thedatamusthavebeensaved insuchawaythatthecolumnsrepresentdatavariables. Editingafilesimplyplacesyouinthespreadsheetdataeditor withoutdestroyingtheexistingdata.Thisalowsforaddingor changingdata. Thehelpdriveselectionallowsyoutochangethedrivepath forfindingthehelpfiles.Uponstartingtheprogramthedrive searchedforthefilesistheonefromwhichtheprogramwas started. The"Tables"selectionsloadinstandardstatisticstablesso thatyoucancheckvaluesagainstthem.Notallpossibletablesare present.TablesarenotusedfortestswhereB/STATisableto calculatetheprobabilitybydirectmathematicalmeans. Thedataeditorisdesignedforefficiententryofdatafor furtheranalysis. Dataisassumedtobeintheformofvariableswhicheach occupyacolumn. Variousoperationscanbeperformedonthevariablesby enteringcommandsonthecommandline. Thefirstgroupaffectthevariableinwhichthecursorislocated. AssumethatvariableYcontainsthecursor.Theoperationsare: a+bVariableYisthesumofvariablesaandb a+xVariableYisthesumofvariableaandconstantx a-b a-x a/bVariableYequalsvariableadividedbyvariableb a/xa*bVariableYequalsvariableatimesvariableb a*x a^bVariableYequalsvariableatothepowerofvariableb a^xVariableYequalsatopowerofconstantx abVariableYis1ifagreaterthanbelse0 a>xVariableYis1ifagreaterthanconstantx a\bVariableYisminimumofaandb a\xVariableYisminimumofaandconstantx a|bVariableYismaxofaandb a|xVariableYismaxofaandconstantx a!bSwapsvariablesaandb.Yisnotaltered a!xSetsvariableatovaluex a@xVariableYisaccumulationofaatx%interest paymentsatendofperiod a&xVariableYisaccumulationofaatx%interest paymentsatstartofperiod a@bVariableYisaccumulationofaatinterestratesgiven incolumnb a&bsameasa@bbutpaymentsatstart a$xVariableYispresentvalueofpaymentsat interestratex%paymentsatendofperiod a$bsameexceptvaryinginterestgiveninb a#xAsfora$xexceptpaymentsatstart a#bAsfora$bexceptpaymentsatstart a%xfindsinternalrateofreturnsuchthatPV ofcolumnaequalsxpaymentsatendofperiod a%bFindsaseriesofyieldratessuchthatthePV ofcolumnaequalsthevalueincolumnb TheresultsgoinY RADTODEG(a)VariableYisconversionofatodegrees degtorad(a)VariableYisconversionofatoradians sort(a)sortsvariableainascendingorderYunused sortall(a,b,c)sortswholedatasetwithkeysa,b,c notallkeysneededbutatleast1 counterxxVariableYisfilledwithacounterfrom1to xx blankVariableYisblankedout mult(a)VariableYisrunningproductofa rot(a)VariableYisrotateda fact(a)variableYisfactorialofa abs(a)VariableYisabsolutevalueofa sqr(a)VariableYissquarerootofa sin(a)VariableYissinofa cos(a)VariableYiscosofa tan(a)VariableYistanofa asin(a)VariableYisarcsinofa asec(a)VariableYisarcsecantofa acos(a)VariableYisarccosofa atn(a)VariableYisarctanofa log(a)VariableYislogofa exp(a)VariableYisetothepowerofa log10(a)VariableYislogtobase10ofa exp10(a)VariableYis10tothepowerofa int(a)VariableYisintegerpartofa asinh(a)VariableYisarchyperbolicsinofa acosh(a)VariableYisarchyperboliccosofa atanh(a)VariableYisarchyperbolictanofa sinh(a)VariableYishyperbolicsinofa cosh(a)VariableYishyperboliccosofa tanh(a)VariableYishyperbolictanofa amort(amount,term,conv,payts,intr) amortizesaloanofamount"amount"over aperiodof"term"years. interestisconvertible"conv"timesperyear thereare"payts"paymentsperyear(iemonthlyis12) theinterestrateisspecifiedinpercentby"intr" >axx Thiscommandcausesthecursortogotocolumn"a"row"xx" Cursormovementscanbemadeusingthearrowkeys.Holdingdownthe "Control"keyandpressingthearrowkeyscausesmovementofafull page. STATS1Menu NormalityTests These2testcheckwhetheravariableisdrawnfromanormal population.Inbothcasesyoumustselectthevariabletooperate on.Inthecasewhereyouknowtheparametersyouwillbeaskedfor themeanandstandarddeviationoftheunderlyingpopulation.The programwillnotevaluatethestatisticreturned.Publishedtables mustbeused DescriptiveStatistics Thesetestsprovidemean,standarddeviation,kurtosisetcfor thedataset.Ifthedataisgroupedyouwillhavetoselecta groupingvariableaswellasthedatavariable. Correlation Theseprovidesimplecorrelationtests.Simplecorrelationis thecorrelationbetween2variableswhichyouchoose.TheSpearman rankcorrelationtestcomparestheranksof2setsofvariables ratherthantheactualnumbers.Thecontingencycoefficienttest compares2variablesonaparametricbasis.Datamustbenon negativeandscalednominally KendalConcordanceisusedwith3ormorevariableswhichareinthe formofranks.Noselectionofvariablesismade.Theentiresetof datainmemoryisused. TheKendalTautestissimilartotheSpearmanranktest.Itisused for2variablesintheformofranks. ThePointBiserialcorrelationtestisusedwith2related variables.Onevariablerepresentstheresultandtheotherthe classificationbasedonadichotomousvariable.Adichotomous variableisonewhichcanhaveonly2values0or1.Forexample maleversusfemale.Youwillbeaskedseparatelyforthe2 variables. LaggedAutocorrelationdeterminesthecorrelationofa variablewithitselfatanearliertime.Theprogramwillaskfor thevariabletobeexaminedandavariableintowhichtostorethe results.Theresultisaseriesofvaluesspecifyingthecorrelation foramultitudeoflagperiods.Thefirstvalueiswith0lagand hasvalue1. LaggedMultipleCorrelationissimilartotheaboveexceptthat 2variablesareexamined.Inthiscaseyouareaskedfor2 variables.Orderofselectionisimportant.Thelagperiodwill refertothevalueofthesecondvariable"K"periodsearlier.Thus ifVariable"A"istoberelatedtoVariable"B"atearlierperiods, youshouldselectVariable"A"firstand"B"second. OrdinalTests KolmogorovSmirnov Checksasinglevariabletodetermineifthevaluessupportthe hypothesisthatthedifferencesbetweenthemarechance. MannWhitney Requires2independentsamples(variables).Thevariablesdo nothavetobethesamesize.Thedatarepresentsaranking.Thetest determineswhetherthereappearstobeadifferencebetweenthe samples.Smallvaluesareextremeforthistestsothecomparison is"isthevaluelessthanthetablevalue?" Wilcoxontest SimilartotheMannWhitneyexceptthatthesamplesare related.LiketheMannWhitney,smallvaluesareextreme.Thusif thecalculatedvalueislessthanthetabularvalueyourejectthe nullhypothesisthatthereisnodifferencebetweensamples. KruskalWallistest Forthistestalldatainthedatasetisused.Theremustbe atleast3variables.Thetestisbasicallythe3ormorefactor equivalenttoMannWhitney.Theextremevaluesarehighunlike theMannWhitney. Friedmantest Alldataisused.Thisisthe3ormorefactorequivalentto theWilcoxontest.Howeverbecauseoftheformulationofthe statisticextremevaluesarehigh. Mediantest 2variablesareselected.Thetestindicateswhetherthe2 samplesappeartobedrawnfrompopulationswiththesamemedian. Runstest Thistestisusedfor1variable.Inadditionyoumustchoose whetherthetestcriteriaiszero,themeanorthemedian.Thetest determineswhetherthedataappearstoberandomlydistributedabout thecriteria. Signtest Youmustchooseavariableandthenatestvalueforthe median.Theprogramcalculatesaprobabilitythatthechosenvalue isindeedthemedianofthepopulationfromwhichthedatais selected. NominalTests ChiSquare1 2Variablesareusedwiththefirstrepresentingtheexpected andthesecondtheactual.Thetestdetermineswhethertheactual dataisconsistantwiththeexpected ChiSquare2 Thistestusesallofthedata.Thedataisassumedtobeset upinacontingencymatrixform.Thenullhypothesisisthatthere isnorelationshipbetweentherowsandcolumns. McNemartest Alldataisused.Theremustbe2rowsand2columns.Itisa testusedtoinvestigatechangesinresponseinapreandpost stimulousstudy.Seethemanualfordatasetup. Cochrantest Alldatainthedatasetisused.Theremustbe3ormore relatedvariables.Thedataisdichotomousinnature.InB/STAT positivesaretreatedas1negativesor0as0.Thetestusesthe nullhypothesisthatthereisnodifferencebetweenvariables.STATS 2MENUITEMS Distributions Thissetofitemscalculatesprobabilitiesforthegiven distributionbaseduponvalueswhichyouinputinresponseto questions.Nodatavariablesareused. TTests Thereare3T-testsavailable.Test1calculatesthechancethat agivenvariablehasacertainmean.Youareaskedtochoosea variableandtospecifyameantotest.Thesecondtestchecksthe chancethat2variableshavethesamemean.Youhavetoselect2 variables.The2variablesshouldberandomlyselectedand unrelated.ThethirdTtestisdesignedfor2variableswhichare related.Onceagainyousimplyselect2variables. Multivariate Thereare2proceduresFactoranalysisand Discriminantanalysis.Thesearesomewhatsimilar.Forfactor analysisyoufirstselectthevariableswhichyouwantinthestudy. Youmustthenselectthetypeofrotationdesired.Ifyouchoosean orthobliquerotationthenanorthobliquefactormustbeentered.The orthobliquefactormustbefrom0to.5 Indiscriminantanalysisyoumustfirstselecttheindependant variables.Younextchoosethedependantvariable. Inbothproceduresthedataentryscreenisusedtodisplay results.Notextinputcanbemadebutallmenufunctionsandarrows work. ANOVA TheAnalysisofVariancesectionallowsforflexibilityindata structure.Theonewaystudiesallrequirethatthedatabesetup inatraditionalANOVAmatrixstructure.Questionswillnotbeasked fortherandom,blockedorlatinsquaredesigns.Fornestedyou willbeaskedtospecifythenumberoftreatmentsinablock. Forthe2and3wayANOVAdesignsthedatacanbeeithersetup inamatrix(thedefault)orseparatevariablescanbeusedto representthelevelsofthevariables.Ina3waydesignnotusing matricesyouwouldbeaskedforthevariablethatheldtheresults andtheninturnforthevariablecontainingthelevelinformation forfactorsABandC.Ifthedatawasinmatrixformyouwouldneed tospecifythenumberoflevelsinAandB. Forthe2factorcasetheinputrequiredissimilar. VarianceTests Theonefactortestasksforavariablenameandavalueto test.Thevaluetestedisthestandarddeviationandtheprogram willgivebackthechanceofthevariablewaschosenfroma populationwiththegivenstandarddeviation.The2factortest compares2variablestodeterminethechancethattheyareboth drawnfromapopulationwiththesamestandarddeviation.  STATS3MENU Regression Thefirst7itemsallhavesimilarinputandoutputstructures. Youwillbeaskedforthevariableswhicharetheindependent variablesandforthe1dependentvariable.Youwillthenbeasked forthevariableintowhichthecalculatedvaluesshouldbeplaced. Theprogramdoesnotplacetheresidualsinavariableaasthiswould restrictthenumberofvariableswhichcouldactuallybeusedinthe regression.Togettheresidualssimplysubtractthecalculateddata fromtheactualinthedataeditor.Thedifferencesliein additionalpartsoftheregressions.TheMultipleregression selectionisatraditionalregression.Ridgeregressionwillrequire theentryofaridgefactorwhichshouldbesmallandbetween0and 1(mostoftenbelow.2) StepwiseregressionislikeMultiple,exceptthatyouspecify allindependentvariablestobeconsidered.Theprogramdecideson whichofthesetoactuallyuseintheregression. CochranreferstoaregressiondoneusingtheCochran-Orcutt procedure.A"Cochran"factorofbetween0and1mustbeused.This typeofregressionactuallyusesapartofthepreviouspointinthe calculation.IftheCochranfactoris1thentheregressionis actuallycalculateduponthefirstdifferencesofthevariables. Huberregressionisusedtoreducetheweightgiventooutliers inthedata.Youwillneedtospecifytwoadditionalpiecesofdata. Thefirstisthevariableintowhichtheprogramplacestheweights andthesecondisthevalueoftheresidualatwhichtheweights shouldstarttobechanged.Thisprocedurecanreallyonlybeused afterfirstdoingatraditionalregression. Weightedregressionrequiresyoutospecifyaweightvariable beforeexecution. ChowregressionisasimplemodificationofMultiple.Itis usedtoseeiftheregressionparametersareconstantoverthescope ofthedatavariables.Youwillhavetospecifythenumberofpoints tokeepinthefirstsample. PrincipleComponentsisnotactuallyaregressionmethodat all.Itisaprocessusedtoreducethenumberofvariablesneeded toexplainthevariationinthedata.Theresultantvariablesare orthogonal;thatisthecorrelationbetweenany2variablesis0. Regressioncanoftenthenbecarriedoutagainstthesepseudo variables.Theprocessisdestructiveinthatitwipesoutthe existingvariables.Eachnewoneisalinearcombinationofthe others. Correlationmatrix Ratherthanafullregressionyoumaysimplywanttoseethe correlationbetweenagroupofvariables.Thisisoftendonetolook attheeffectsofmulticolinearityonthedata. TimeSeries  Thesearemethodsofsmoothingorprojectingdata.Theyareoften usedincombinationwithotherprocedures. Movingaveragerequiresyoutochoosethevariableandthe periodofthemovingaverage.Aswellyoumustselectavariable intowhichtheaveragedvariablewillbeplaced. Geometricmovingaveragesrequirethesameinputaslinear movingaverages. Fouriersmoothingrequiresavariabletosmoothandavariable toplacetheresult.Italsoasksforthenumberoftermstobekept intheintermediatecalculations.Thisvalueshouldbelessthan50, usuallylesthan15.Theremustbenomissingdataforthis proceduretowork.Notethatthiscanbeaslowprocess. Brown1wayexponentialsmoothing Thisissimpleexponentialsmoothing.Youwillbeaskedto specifythevariabletosmoothandavariabletostoretheresult. Inadditionyouwillneedasmoothingconstant(0to1)anda startingvalue.Ifyoudonotspecifythestartingvaluetheprogram willgenerateone.Thisprocessisnotdesignedfordatawitha distibcttrendline.Ifthereisadistinctlineartrendthen2way exponentialsmoothingshouldbeused. Brown's2wayexponentialsmoothinguseslinearregressionto estimateastartingvalueandtrend.Youmustestimatethesmoothing coefficientandvariabletosmoothandvariableforresult. Holt's2wayexponentialsmoothingissimilartoBrown'sexcept thataseparatesmoothingcoefficientisusedforthetrendfactor. Ifthereisaseasonalaspecttothedata(likeretailsales whichhaveaDecemberpeak)thenWinter'sexponentialsmoothing shouldbeused.Youwillhavetoenter4quantities.Thefirstis thesmoothingcoefficientforlevel.Thesecondisfortrend.The thirdisforseasonality.Thefourthvalueistheperiodof seasonality.Notethatthismethodshouldnotbeusedifthedata fluctuatesaboveandbelowzero.Ifthedatadoesgobelowzeroand youwanttousethismethodaddaconstanttothedatatomakeit allpositive.Thenaftersmoothingsubtracttheconstant. Interpolation B/STATuses3formsofestimatingunavailabledata.Thefirst issimplelinearinterpolation.Forthisyousimplyselectthe variable.ThesecondisLagrangianinterpolation.Forthisyouneed 2variables;an"X"variableanda"Y"variable.Therecanbeno missing"X"variables.Thethirdmethodisthemethodofcubic splines.Thisprocedureassumesthatthedataintheselected variableconsistsofeavenlyspacedobservations.Notethat Langrangianinterpolationcanbeslowifthereisalotofdata sinceeachpointisusedinestimatingmissingdata. Extract Theseselectionsallowyoutoreducetheamountofdatainthe dataset.Thefirstoptionsumsthedata.Forexampleifyouwantto getyearlytotalsfromadatasetofmonthlydatayoucanextract summeddataandreducethedatabyafactorof12.Eachelement wouldthenbeayearlytotal.Inthenonsummedcaseonlyevery12th valuewouldbeleft.Nosummingwouldbedone.Thisisusefullif youwanttolookatsubstesinisolation. Miscellaneous Thismenuhastwoproceduresinadditiontotheusualhelp selection. Crosstabs Thisprocedureisusedtosummarizedatawhichliesin2or threevariables.Itproducesacountforthecombinationofvalues inthechosenvariables.Forexampleyoumayhavedataonthe heightandweightofagroupofarmyrecruits.Youcoulduse crosstabstofindoutthenuberineachheightandweight classificationwherethesecouldbeheightin2inchincrements andweightin5poundincrements.Itismostcommonlyused inmarketresearchforcrossessuchasbetweenage30and34and earningbetween20and30000dollarsperyear. Youfirstselectthevariablestouseinthecrosstab. Ifyouselect2thena2waycrosstabisdone.If3thena3way crosstabisdone.Nextyouselectthebreakpointsfortheclasses ineachvariable.Theremaybe14breakpointsgiving15classes maximumforeach.Youneedonlytypeinasmanybreakpointsas thereareandleavetherestblank.Thenumberofbreakpointscan bedifferentforeachvariable.Notethatthelowerclass includesthebreakpoint.Thusabreakpointof200poundswould put200poundpeopleinthelowerclassand200.01poundpeople inthehigherclass.Theprogramwillprintouttheresults.Ifyou wantyoumayreplacethedatainmemorywiththesummarized totals.Thiscanbequiteusefullifyouthenwanttoperformachi squaretesttype2ontheresulttoseeifthereareany significantrelationships. Difference Thisprocessisquitesimple.Thedifferenceofavariable issimplyitschangefromoneperiodtothenext.Sometimes someprocedureswillworkbetteronthechangeinavariable ratherthanthevariableitself.ThisisespeciallytrueinBox Jenkinsanalysis. Theinputisquitesimple.Youareaskedthevariableto differenceandthevariableintowhichtoplacetheresult. GRAPHICS Graphmenu Theregularselectionwillgraphthedatawiththelabelsyou haveenteredinthedataentryareaalongthe"X"axis.Thetypeof graphwilldependontheselectionsyouhavemadeinthe"styles" area.Upto6variablesmaybechosen.Youmayplotsomeagainstthe leftaxisandsomeagainsttherightaxis.Thehorizontalgraph optionputsthelabelsonthe"Y"axisandthevaluesalongthe"X". Youcannothavearightsideaxisforthistypeofgraph. "XY"graphsallowupto6pairsofvariablestobeused.You mustselectyourdataapairatatime.Thefirstonechosenofeach pairwillbethe"X"valueofthepointandthesecondwillbethe "Y".Youmayrepeatthesameselectionbetweenpairssothatyoucan haveseveralvariablesgraphedagainstthesame"X".TherearenoXY bargraphs.Youcannothavearightsideaxis. HILOgraphsarestockmarketgraphs.Thefirst3variables chosenwillbedisplayedasahighlowclosetypeofgraph.The remainderofthe6possiblegraphswillbeshownasselectedonthe stylessection.Youcanuserightsideaxiswhichallowsyouto graphvolumeonthesamegraphasstockprices.Youcanhaveahi lowgraphwithonly2variables.Inthiscasethedatarepresents simplyahiandlowbutnoclose. Piecharts.Youmayhaveupto4piesonthescreen.Simply specifythecorrectnumberofvariables.Aspecialcaseexistsfor2 piechartsifyouhaveselected"componentpies"fromthefeatures menu.Inthiscasethesecondvariablewillbeassumedtobean explosionofthefirstpiesegment.Bubblegraphsrequire3 variablestobechosen.Thefirstspecifiesthe"X"valueofthe point.Thesecondspecifiesthe"Y"valueofthepointandthethird specifiestherelativeareaofthebubble. OPPOSEDBARSrequire2variableswhichmustbepositive. Iflogsareontheyareignored.Opposedbarsaregoodfor comparingsimilardataagainstoneanother.anexamplemightbe thepopulationoftheU.S.A.byagegroupwhereone variablerepresentsmalesandanotherfemales.Thekeyfeature ofopposedbarsisthatthereisnooffsetbetweenthevariables. Onepeculiarityoftheimplementationcomesupinrescaling. Thesecondvariableistreatedasbeingnegativebythe program.Thustheminimumvalueisshownasanegative.This isarequirementsoensurethatyouenteranegativeforthe minimum,eventhoughitwillbeprintedasapositive. FLOATINGBARSrequire2variablesforeachbarplotted. Thefirstrepresentstheminimumofthefloatingbarandthe secondthetop.LikeXYgraphsyouwillcontinuetobepromptedfor inputuntilyoufailtoenter2variables.ThisisnotanXY graphhowever.TheX-axisisscaledbythelabelsjustasfora regulargraph. HORIZONTALFLOATINGBARSarethesameasregularfloating barsexceptthatthegraphisdonehorizontally. STATGRAF Theseproceduresareparticulargraphtypesusedforanalysis. Astargraphproducesachartdescribingthephysicalvaluesof severalvariablesateachofseveralpoints.Thereshouldbeno negativevalues.Foreachpointaseriesoflinesaredrawnstarting at3O'clockandthenworkingcounterclockwisearoundthepoint. Thelengthofthelinesrepresentshowhighthevalueofthe variableisforthatpoint.Theminimumvalueofthelineissetto 20percentofthemaximum. Asunraygraphissimilarinconcept.Inthiscaseeachline isthesamelengthbutthelineiscutatavalueindicating relativelength.Ifthelineiscutexactlyinthemiddlethenthe pointhasavalueforthatvariablewhichisatthemeanforall points.Aboxwhiskergraphrequirestheselectionofavariableand acategoryvariable.Theboxandwhiskerarethendrawnforvalues fromthefirstvariablewherethecategoricalvariableisata certainlevel.Theboxandwhiskerisaregularstylegraph.Thebox hasit'stopvaluatthe3rdquartilepointanditsbottomatthe firstquartile.Theboxisbisectedbyalineatthemedian. Extendingoutfromtheboxattopandbottomarethewhiskers.These reachouttothehighestandlowestpointinthedatavariablefora givenlevelofthecategoricalvariable. Thenotchedboxwhiskeristhesameexceptthatthereisan additionalpieceofinformationgiven.Thereisanotchinthebox whichcoversa95percentconfidencelimitonthemedian.Thedepth ofthenotchisproportionaltothenumberofelementsinthe variablewiththatvalueofthecategoricalvariable. SETTINGS Thesettingsmenuallowsyoutodefinehowthegraphwilllook. Thepalettesettingallowsyoutosetthepaletteforthegraph. Stlesallowssettingthelinestylefillpatternandpointstyle.It alsoallowsyoutoturnonlinesbarsorpoints.All3canbeonfor anygivenvariable.PieStyleallowsyoutosetcolorsandfill stylesforpiesaswellaswhetherasliceisexploded.Axesallows turningscalingoraxesonandoffaswellasselectingthecolorto beused.Titlesallowsyoutoenterthetitlestobeusedonthe graph.TitleFontsallowsyoutoselectthecolorandstyleofthe maintitleandthesubtitle. Features Boxedmeansthatforregularandhorizontalgraphsalinewill bedrawntocloseinthegraph.Rtsideaxiswillallowarightside axisonregulargraphs. Stackedwillgivestackedbargraphsandareagraphsforline graphs. Filledwillcausetheareabetweenlinestobefilledin.It cannotbecombinedwithstacked. Valsabovewillcausethevalueofthepointtobedisplayed aboveitforregularandhorizontalgraphs.ForPiechartsthe valueswillbeprintedbelowthepielabel. Legendwilcausethelegendforeachvariabletobedisplayed. Ifturnedoffthenthegraphwillbelargerbutyouwillhavetouse customlabellingtodefinewhatthevariablesare.  LogXcausestheXaxistobeonaLOGbasis. LogYdoesthesamefortheYaxis. ProportionalPiemeansthatifmorethan1pieisshownonthe screenatoncethererelativesizeswillbedeterminedbythetotal ofthevaluesineachpie.Thisisquiteusefullwhencomparing4 yearsofsalesdata. ComponentPie.When2variablesareselectedforapiegraph thisoptioncausesthesecondvariabletobetakenasasubsetof thefirstpiesector.Thevaluesinthesecondvariableare displayedasastackedbarsettotherightofthepie. PiePercentwillcausethepercentageeachpieslice representstobeprintedinthepieslice.Thepercentis roundedtothenearestwholepercentage. Grids Thesetwooptionsturnonhorizontalandverticalgrids.There isalsoa"zeroline"optiontoensurethatalineisdrawnatthe zeropointevenifnogridsaredisplayed. Whileagraphisonscreenlabelsmaybeaddedbydouble clickingwhereyouwantthemtoappear.Youwillberequiredto selectthefontandsizeforthelabeljustasfortitles.You havetheoptionofaddinganarrow.Simplyclickwhereyouwantit topoint.Theselabelsmaybedraggedonthescreen.To removeafloatinglabel,doubleclickonthelabel.Youarenow asked"WhattoChange?".Thiscanbeeitherfont,text,or arrow.Youcanremovethelabelbyselectingtextanderasingthe existingtext.alabelwithnotextissimplyremovedfrom thelistoflabels.Ifyouchoosearrowyoucaneitheraddan arrowifonedoesnotexistormovetheanchorpointforan existingarrow,orremovethearrow. Themenubardisplayedwhileagraphisonscreenallowsyou tosaveorprintthegraph.Selecting"SAVE"willcreateaDegas uncompressedimageonyourdisk.Whenprintingyouhavethree options.FirstyoucanprintthescreenusingthebuiltinAtari screendumputilityoronewhichyouhaveloadedyourself.The secondoptionisusefullonlyfor9pinEpsonprinters.This optionusestheEpsonplottermodetoensureproperlyscaled pictures.Italsoonlyworkswiththemonochromemonitor.Thelast choiceusesGDOSifyouhaveittoplottotheprinter.Thetexton thegraphwillnotusuallylookquitethesameasonthescreen sincemanyGDOSfontsareproportionalandthedefaultscreen fontsarenot.Alsosomeoftheprinterfontsarenotquitethe samesizeasthescreenfonts. Alsoonthisscreenyoucanrescalethegraph.Selections existforrescalingtheX-axis,oreitherY-axis.Youmust inputthemaximum,minimum,distancebetweenlabelsanddistance betweentics.Themiscellaneousmenuallowsyoutoreturneither tothetopmenuortothegraphselectionmenu.Another selectionallowsyoutochoosewhetheryouwantfloatinglabels erasedonexitormaintained.  The main menu area is used for travelling between menus and for loading and creating files. Creating files first requests information on the type of label to be used for the data. These labels are only used for graphing. They do not have any impact on the statistical procedures in the program. They may be initialized as blanks, to be filled in later by you. They may simply be a counter in which case you will be asked to specify the starting value and a rate of increment. This option would be used if you wanted to specify calendar years such as 1988. You may select months as a label. In this case you must enter a numeric value for the month such as 1 for January etc. The data may be specified as days of the week or weekdays. The difference between these 2 is that days of the week includes Saturday and Sunday, while week days includes only Monday to Friday. For each of these options you have 13 different ways in which the date may be shown. These are displayed in a grid of 27 squares on the screen. Clicking the mouse button on one of the squares will hilight the style. a subsequent click will return the square to normal. Clicking on EXIT will make the choice official. This style of dialog box is used throughout B/STAT for selecting variables. After selecting the style you must specify the date information about the starting day for the data. These values must be specified numerically. The week is assumed to start on Monday so 1 is Monday and 7 is Sunday. If you enter an impossible month such as month 23 the program will take the modulus of 12 and this number to generate the starting month. Similar actions occur for the day and the day of the week. Years may be entered as 1988 or as simply 88. Any number below 100 is treated as 1900+ the number; any negative numbers are converted to positives so unfortunately years such as 34BC will have to be typed as manual labels. Once the type of label is entered you will move to the spreadsheet style data entry screen. This screen allows for 26 columns of data and as many rows as you initialized in the program. The minimum number of data rows is 19. B/STAT is not a spreadsheet. This screen is simply for data entry although some facility for variable creation does exist. The spreadsheet uses both menu drop downs and commands for operation. For rapid movement around the spreadsheet the ">" command is used. >s45 will move the cursor to column "S" and row 45 automatically. As well there are commands for sorting columns, adding them together etc. The command list is available by selecting the help menu from the data entry screen. For missing data enter NA as the value. The normal view of the columns in the spreadsheet is as separate data variables. There are statistical procedures however in B/STAT which treat the entire collection of data as a matrix of data. These procedures are discussed more fully in the manual and in the individual help screens. B/STAT allows for saving and loading different data formats. Straight save and load do so in B/STAT's format. DIF load and save do so in the data interchange format introduced by VISICALC many years ago and currently supported by most programs. B/STAT will ask you if you want to load the data by column or row. Strictly speaking the question is misleading. In the original DIF standard you could save the data by row or by column. Many programs today give you no such choice so you can not tell whether the variables were saved as rows or columns. Similarily neither can B/STAT. It can not know whether the data represents 12 variables with 20 points each or 20 variables with 12 points each. We suggest that you try loading data by column and then checking to see if it came in properly. If not then reload by row. From then on you will know that data from that program must be loaded into B/STAT in that fashion. Note that B/STAT can accept only numeric data in a DIF file. An ASCII file refers to a file where each record is a number. To be used by B/STAT the data must be in the following order #rows used #columns used data value for col 1 row 1 data value for col 2 row 1 data value for col 3 row 1 etc PRN files are created by many spreadsheet programs. These are actual disk images of pages which would otherwise have been printed. Only numerics are allowed in B/STAT. The data must have been saved in such a way that the columns represent data variables. Editing a file simply places you in the spreadsheet data editor without destroying the existing data. This alows for adding or changing data. The help drive selection allows you to change the drive path for finding the help files. Upon starting the program the drive searched for the files is the one from which the program was started. The "Tables" selections load in standard statistics tables so that you can check values against them. Not all possible tables are present. Tables are not used for tests where B/STAT is able to calculate the probability by direct mathematical means. The data editor is designed for efficient entry of data for further analysis. Data is assumed to be in the form of variables which each occupy a column. Various operations can be performed on the variables by entering commands on the command line. The first group affect the variable in which the cursor is located. Assume that variable Y contains the cursor. The operations are: a+b Variable Y is the sum of variables a and b a+x Variable Y is the sum of variable a and constant x a-b a-x a/b Variable Y equals variable a divided by variable b a/x a*b Variable Y equals variable a times variable b a*x a^b Variable Y equals variable a to the power of variable b a^x Variable Y equals a to power of constant x ab Variable Y is 1 if a greater than b else 0 a>x Variable Y is 1 if a greater than constant x a\b Variable Y is minimum of a and b a\x Variable Y is minimum of a and constant x a|b Variable Y is max of a and b a|x Variable Y is max of a and constant x a!b Swaps variables a and b. Y is not altered a!x Sets variable a to value x a@x Variable Y is accumulation of a at x% interest payments at end of period a&x Variable Y is accumulation of a at x% interest payments at start of period a@b Variable Y is accumulation of a at interest rates given in column b a&b same as a@b but payments at start a$x Variable Y is present value of payments at interest rate x% payments at end of period a$b same except varying interest given in b a#x As for a$x except payments at start a#b As for a$b except payments at start a%x finds internal rate of return such that PV of column a equals x payments at end of period a%b Finds a series of yield rates such that the PV of column a equals the value in column b The results go in Y RADTODEG(a) Variable Y is conversion of a to degrees degtorad(a) Variable Y is conversion of a to radians sort(a) sorts variable a in ascending order Y unused sortall(a,b,c) sorts whole data set with keys a,b,c not all keys needed but at least 1 counterxx Variable Y is filled with a counter from 1 to xx blank Variable Y is blanked out mult(a) Variable Y is running product of a rot(a) Variable Y is rotated a fact(a) variable Y is factorial of a abs(a) Variable Y is absolute value of a sqr(a) Variable Y is square root of a sin(a) Variable Y is sin of a cos(a) Variable Y is cos of a tan(a) Variable Y is tan of a asin(a) Variable Y is arcsin of a asec(a) Variable Y is arcsecant of a acos(a) Variable Y is arccos of a atn(a) Variable Y is arctan of a log(a) Variable Y is log of a exp(a) Variable Y is e to the power of a log10(a) Variable Y is log to base 10 of a exp10(a) Variable Y is 10 to the power of a int(a) Variable Y is integer part of a asinh(a) Variable Y is arc hyperbolic sin of a acosh(a) Variable Y is arc hyperbolic cos of a atanh(a) Variable Y is arc hyperbolic tan of a sinh(a) Variable Y is hyperbolic sin of a cosh(a) Variable Y is hyperbolic cos of a tanh(a) Variable Y is hyperbolic tan of a amort(amount,term,conv,payts,intr) amortizes a loan of amount "amount" over a period of "term" years. interest is convertible "conv" times per year there are "payts" payments per year (ie monthly is 12) the interest rate is specified in percent by "intr" >axx This command causes the cursor to go to column "a" row "xx" Cursor movements can be made using the arrow keys. Holding down the "Control" key and pressing the arrow keys causes movement of a full page. STATS 1 Menu Normality Tests These 2 test check whether a variable is drawn from a normal population. In both cases you must select the variable to operate on. In the case where you know the parameters you will be asked for the mean and standard deviation of the underlying population. The program will not evaluate the statistic returned. Published tables must be used Descriptive Statistics These tests provide mean, standard deviation, kurtosis etc for the data set. If the data is grouped you will have to select a grouping variable as well as the data variable. Correlation These provide simple correlation tests. Simple correlation is the correlation between 2 variables which you choose. The Spearman rank correlation test compares the ranks of 2 sets of variables rather than the actual numbers. The contingency coefficient test compares 2 variables on a parametric basis. Data must be non negative and scaled nominally Kendal Concordance is used with 3 or more variables which are in the form of ranks. No selection of variables is made. The entire set of data in memory is used. The Kendal Tau test is similar to the Spearman rank test. It is used for 2 variables in the form of ranks. The Point Biserial correlation test is used with 2 related variables. One variable represents the result and the other the classification based on a dichotomous variable. A dichotomous variable is one which can have only 2 values 0 or 1. For example male versus female. You will be asked separately for the 2 variables. Lagged Auto correlation determines the correlation of a variable with itself at an earlier time. The program will ask for the variable to be examined and a variable into which to store the results. The result is a series of values specifying the correlation for a multitude of lag periods. The first value is with 0 lag and has value 1. Lagged Multiple Correlation is similar to the above except that 2 variables are examined. In this case you are asked for 2 variables. Order of selection is important. The lag period will refer to the value of the second variable "K" periods earlier. Thus if Variable "A" is to be related to Variable "B" at earlier periods, you should select Variable "A" first and "B" second. Ordinal Tests Kolmogorov Smirnov Checks a single variable to determine if the values support the hypothesis that the differences between them are chance. Mann Whitney Requires 2 independent samples (variables). The variables do not have to be the same size. The data represents a ranking.The test determines whether there appears to be a difference between the samples. Small values are extreme for this test so the comparison is "is the value less than the table value?" Wilcoxon test Similar to the Mann Whitney except that the samples are related. Like the Mann Whitney, small values are extreme. Thus if the calculated value is less than the tabular value you reject the null hypothesis that there is no difference between samples. Kruskal Wallis test For this test all data in the data set is used. There must be at least 3 variables. The test is basically the 3 or more factor equivalent to Mann Whitney. The extreme values are high unlike the Mann Whitney. Friedman test All data is used. This is the 3 or more factor equivalent to the Wilcoxon test. However because of the formulation of the statistic extreme values are high. Median test 2 variables are selected. The test indicates whether the 2 samples appear to be drawn from populations with the same median. Runs test This test is used for 1 variable. In addition you must choose whether the test criteria is zero, the mean or the median. The test determines whether the data appears to be randomly distributed about the criteria. Sign test You must choose a variable and then a test value for the median. The program calculates a probability that the chosen value is indeed the median of the population from which the data is selected. Nominal Tests Chi Square 1 2 Variables are used with the first representing the expected and the second the actual. The test determines whether the actual data is consistant with the expected Chi Square 2 This test uses all of the data. The data is assumed to be set up in a contingency matrix form. The null hypothesis is that there is no relationship between the rows and columns. McNemar test All data is used. There must be 2 rows and 2 columns. It is a test used to investigate changes in response in a pre and post stimulous study. See the manual for data set up. Cochran test All data in the data set is used. There must be 3 or more related variables. The data is dichotomous in nature. In B/STAT positives are treated as 1 negatives or 0 as 0. The test uses the null hypothesis that there is no difference between variables. STATS 2 MENU ITEMS Distributions This set of items calculates probabilities for the given distribution based upon values which you input in response to questions. No data variables are used. T Tests There are 3 T-tests available. Test1 calculates the chance that a given variable has a certain mean. You are asked to choose a variable and to specify a mean to test. The second test checks the chance that 2 variables have the same mean. You have to select 2 variables. The 2 variables should be randomly selected and unrelated. The third T test is designed for 2 variables which are related. Once again you simply select 2 variables. Multivariate There are 2 procedures Factor analysis and Discriminant analysis. These are somewhat similar. For factor analysis you first select the variables which you want in the study. You must then select the type of rotation desired. If you choose an orthoblique rotation then an orthoblique factor must be entered. The orthoblique factor must be from 0 to .5 In discriminant analysis you must first select the independant variables. You next choose the dependant variable. In both procedures the data entry screen is used to display results. No text input can be made but all menu functions and arrows work. ANOVA The Analysis of Variance section allows for flexibility in data structure. The one way studies all require that the data be set up in a traditional ANOVA matrix structure. Questions will not be asked for the random ,blocked or latin square designs. For nested you will be asked to specify the number of treatments in a block. For the 2 and 3 way ANOVA designs the data can be either set up in a matrix (the default) or separate variables can be used to represent the levels of the variables. In a 3 way design not using matrices you would be asked for the variable that held the results and then in turn for the variable containing the level information for factors A B and C. If the data was in matrix form you would need to specify the number of levels in A and B. For the 2 factor case the input required is similar. Variance Tests The one factor test asks for a variable name and a value to test. The value tested is the standard deviation and the program will give back the chance of the variable was chosen from a population with the given standard deviation. The 2 factor test compares 2 variables to determine the chance that they are both drawn from apopulation with the same standard deviation. STATS 3 MENU Regression The first 7 items all have similar input and output structures. You will be asked for the variables which are the independent variables and for the 1 dependent variable. You will then be asked for the variable into which the calculated values should be placed. The program does not place the residuals in avariable aas this would restrict the number of variables which could actually be used in the regression. To get the residuals simply subtract the calculated data from the actual in the data editor. The differences lie in additional parts of the regressions. The Multiple regression selection is a traditional regression. Ridge regression will require the entry of a ridge factor which should be small and between 0 and 1 (most often below .2) Stepwise regression is like Multiple, except that you specify all independent variables to be considered. The program decides on which of these to actually use in the regression. Cochran refers to a regression done using the Cochran-Orcutt procedure. A "Cochran" factor of between 0 and 1 must be used. This type of regression actually uses a part of the previous point in the calculation. If the Cochran factor is 1 then the regression is actually calculated upon the first differences of the variables. Huber regression is used to reduce the weight given to outliers in the data. You will need to specify two additional pieces of data. The first is the variable into which the program places the weights and the second is the value of the residual at which the weights should start to be changed. This procedure can really only be used after first doing a traditional regression. Weighted regression requires you to specify a weight variable before execution. Chow regression is a simple modification of Multiple. It is used to see if the regression parameters are constant over the scope of the data variables. You will have to specify the number of points to keep in the first sample. Principle Components is not actually a regression method at all. It is a process used to reduce the number of variables needed to explain the variation in the data. The resultant variables are orthogonal; that is the correlation between any 2 variables is 0. Regression can often then be carried out against these pseudo variables. The process is destructive in that it wipes out the existing variables. Each new one is a linear combination of the others. Correlation matrix Rather than a full regression you may simply want to see the correlation between a group of variables. This is often done to look at the effects of multicolinearity on the data. Time Series These are methods of smoothing or projecting data. They are often used in combination with other procedures. Moving average requires you to choose the variable and the period of the moving average. As well you must select a variable into which the averaged variable will be placed. Geometric moving averages require the same input as linear moving averages. Fourier smoothing requires a variable to smooth and a variable to place the result. It also asks for the number of terms to be kept in the intermediate calculations. This value should be less than 50, usually les than 15. There must be no missing data for this procedure to work. Note that this can be a slow process. Brown 1 way exponential smoothing This is simple exponential smoothing. You will be asked to specify the variable to smooth and a variable to store the result. In addition you will need a smoothing constant (0 to 1) and a starting value. If you do not specify the starting value the program will generate one. This process is not designed for data with a distibct trend line. If there is a distinct linear trend then 2 way exponential smoothing should be used. Brown's 2 way exponential smoothing uses linear regression to estimate a starting value and trend. You must estimate the smoothing coefficient and variable to smooth and variable for result. Holt's 2 way exponential smoothing is similar to Brown's except that a separate smoothing coefficient is used for the trend factor. If there is a seasonal aspect to the data (like retail sales which have a December peak) then Winter's exponential smoothing should be used. You will have to enter 4 quantities. The first is the smoothing coefficient for level. The second is for trend. The third is for seasonality. The fourth value is the period of seasonality. Note that this method should not be used if the data fluctuates above and below zero. If the data does go below zero and you want to use this method add a constant to the data to make it all positive. Then after smoothing subtract the constant. Interpolation B/STAT uses 3 forms of estimating unavailable data. The first is simple linear interpolation. For this you simply select the variable. The second is Lagrangian interpolation. For this you need 2 variables; an "X" variable and a "Y" variable. There can be no missing "X" variables. The third method is the method of cubic splines. This procedure assumes that the data in the selected variable consists of eavenly spaced observations. Note that Langrangian interpolation can be slow if there is a lot of data since each point is used in estimating missing data. Extract These selections allow you to reduce the amount of data in the data set. The first option sums the data. For example if you want to get yearly totals from a data set of monthly data you can extract summed data and reduce the data by a factor of 12. Each element would then be a yearly total. In the non summed case only every 12th value would be left. No summing would be done. This is usefull if you want to look at substes in isolation. Miscellaneous This menu has two procedures in addition to the usual help selection. Crosstabs This procedure is used to summarize data which lies in 2 or three variables. It produces a count for the combination of values in the chosen variables. For example you may have data on the height and weight of a group of army recruits. You could use crosstabs to find out the nuber in each height and weight classification where these could be height in 2 inch increments and weight in 5 pound increments. It is most commonly used in market research for crosses such as between age 30 and 34 and earning between 20 and 30000 dollars per year. You first select the variables to use in the crosstab. If you select 2 then a 2 way crosstab is done. If 3 then a 3 way crosstab is done. Next you select the break points for the classes in each variable. There may be 14 breakpoints giving 15 classes maximum for each. You need only type in as many breakpoints as there are and leave the rest blank. The number of break points can be different for each variable. Note that the lower class includes the break point. Thus a breakpoint of 200 pounds would put 200 pound people in the lower class and 200.01 pound people in the higher class. The program will print out the results. If you want you may replace the data in memory with the summarized totals. This can be quite usefull if you then want to perform a chi square test type 2 on the result to see if there are any significant relationships. Difference This process is quite simple. The difference of a variable is simply its change from one period to the next. Sometimes some procedures will work better on the change in a variable rather than the variable itself. This is especially true in Box Jenkins analysis. The input is quite simple. You are asked the variable to difference and the variable into which to place the result. GRAPHICS Graph menu The regular selection will graph the data with the labels you have entered in the data entry area along the "X" axis. The type of graph will depend on the selections you have made in the "styles" area. Up to 6 variables may be chosen. You may plot some against the left axis and some against the right axis. The horizontal graph option puts the labels on the "Y" axis and the values along the "X". You can not have a right side axis for this type of graph. "XY" graphs allow up to 6 pairs of variables to be used. You must select your data a pair at a time. The first one chosen of each pair will be the "X" value of the point and the second will be the "Y". You may repeat the same selection between pairs so that you can have several variables graphed against the same "X". There are no XY bar graphs. You can not have a right side axis. HI LO graphs are stock market graphs. The first 3 variables chosen will be displayed as a high low close type of graph. The remainder of the 6 possible graphs will be shown as selected on the styles section. You can use right side axis which allows you to graph volume on the same graph as stock prices. You can have a hi low graph with only 2 variables. In this case the data represents simply a hi and low but no close. Pie charts. You may have up to 4 pies on the screen. Simply specify the correct number of variables. A special case exists for 2 pie charts if you have selected "component pies" from the features menu. In this case the second variable will be assumed to be an explosion of the first pie segment. Bubble graphs require 3 variables to be chosen. The first specifies the "X" value of the point. The second specifies the "Y" value of the point and the third specifies the relative area of the bubble. OPPOSED BARS require 2 variables which must be positive. If logs are on they are ignored. Opposed bars are good for comparing similar data against one another. an example might be the population of the U.S.A. by age group where one variable represents males and another females. The key feature of opposed bars is that there is no offset between the variables. One peculiarity of the implementation comes up in rescaling. The second variable is treated as being negative by the program. Thus the minimum value is shown as a negative. This is a requirement so ensure that you enter a negative for the minimum, even though it will be printed as a positive. FLOATING BARS require 2 variables for each bar plotted. The first represents the minimum of the floating bar and the second the top. Like XY graphs you will continue to be prompted for input until you fail to enter 2 variables. This is not an XY graph however. The X-axis is scaled by the labels just as for a regular graph. HORIZONTAL FLOATING BARS are the same as regular floating bars except that the graph is done horizontally. STAT GRAF These procedures are particular graph types used for analysis. A star graph produces a chart describing the physical values of several variables at each of several points. There should be no negative values. For each point a series of lines are drawn starting at 3 O'clock and then working counterclock wise around the point. The length of the lines represents how high the value of the variable is for that point. The minimum value of the line is set to 20 percent of the maximum. A sun ray graph is similar in concept. In this case each line is the same length but the line is cut at a value indicating relative length. If the line is cut exactly in the middle then the point has a value for that variable which is at the mean for all points. A box whisker graph requires the selection of a variable and a category variable. The box and whisker are then drawn for values from the first variable where the categorical variable is at a certain level. The box and whisker is a regular style graph. The box has it's top valu at the 3rd quartile point and its bottom at the first quartile. The box is bisected by a line at the median. Extending out from the box at top and bottom are the whiskers. These reach out to the highest and lowest point in the data variable for a given level of the categorical variable. The notched box whisker is the same except that there is an additional piece of information given. There is a notch in the box which covers a 95 percent confidence limit on the median. The depth of the notch is proportional to the number of elements in the variable with that value of the categorical variable. SETTINGS The settings menu allows you to define how the graph will look. The palette setting allows you to set the palette for the graph. Stles allows setting the line style fill pattern and point style. It also allows you to turn on lines bars or points. All 3 can be on for any given variable. Pie Style allows you to set colors and fill styles for pies as well as whether a slice is exploded. Axes allows turning scaling or axes on and off as well as selecting the color to be used. Titles allows you to enter the titles to be used on the graph. Title Fonts allows you to select the color and style of the main title and the subtitle. Features Boxed means that for regular and horizontal graphs a line will be drawn to close in the graph. Rt side axis will allow a right side axis on regular graphs. Stacked will give stacked bar graphs and area graphs for line graphs. Filled will cause the area between lines to be filled in. It can not be combined with stacked. Vals above will cause the value of the point to be displayed above it for regular and horizontal graphs. For Pie charts the values will be printed below the pie label. Legend wil cause the legend for each variable to be displayed. If turned off then the graph will be larger but you will have to use custom labelling to define what the variables are. Log X causes the X axis to be on a LOG basis. Log Y does the same for the Y axis. Proportional Pie means that if more than 1 pie is shown on the screen at once there relative sizes will be determined by the total of the values in each pie. This is quite usefull when comparing 4 years of sales data. Component Pie. When 2 variables are selected for a pie graph this option causes the second variable to be taken as a subset of the first pie sector. The values in the second variable are displayed as a stacked bar set to the right of the pie. Pie Percent will cause the percentage each pie slice represents to be printed in the pie slice. The percent is rounded to the nearest whole percentage. Grids These two options turn on horizontal and vertical grids. There is also a "zero line" option to ensure that a line is drawn at the zero point even if no grids are displayed. While a graph is on screen labels may be added by double clicking where you want them to appear. You will be required to select the font and size for the label just as for titles. You have the option of adding an arrow. Simply click where you want it to point. These labels may be dragged on the screen. To remove a floating label, double click on the label. You are now asked "What to Change?". This can be either font, text, or arrow. You can remove the label by selecting text and erasing the existing text. a label with no text is simply removed from the list of labels. If you choose arrow you can either add an arrow if one does not exist or move the anchor point for an existing arrow, or remove the arrow. The menu bar displayed while a graph is on screen allows you to save or print the graph. Selecting "SAVE" will create a Degas uncompressed image on your disk. When printing you have three options. First you can print the screen using the built in Atari screen dump utility or one which you have loaded yourself. The second option is usefull only for 9 pin Epson printers. This option uses the Epson plotter mode to ensure properly scaled pictures. It also only works with the monochrome monitor. The last choice uses GDOS if you have it to plot to the printer. The text on the graph will not usually look quite the same as on the screen since many GDOS fonts are proportional and the default screen fonts are not. Also some of the printer fonts are not quite the same size as the screen fonts. Also on this screen you can rescale the graph. Selections exist for rescaling the X-axis, or either Y-axis. You must input the maximum, minimum, distance between labels and distance between tics. The miscellaneous menu allows you to return either to the top menu or to the graph selection menu. Another selection allows you to choose whether you want floating labels erased on exit or maintained.