NNNNNNB>p NNNNNNNNNNNNNNNNNNNNNNNNNNNNNNONNNNNNNNNNNNNNNNNNNNNN /@`!#o'+-//3@59;=?A C@E`MOQ S@U`WY[]_a c@e`gikmoq s@u`wy{} @` @ ` @ ` @ ` @ ` ǀ ɠ @ ` ׀ ٠  @` @`!Aa   !Aa!!#A%a')+-/1!3A5a79;=?A!CAEaGIKMOQ!SAUaWY[]_a!cAeagikmoq!sAuawy{}!Aa!Aa!Aa!Aa!Aaǁɡ!Aaׁ١!Aa!Aa " B b  !"!B!b!!!!!"!""#B"%b"'")"+"-"/#1"#5b#7#9#;#=#?$A"$CB$Eb$G$I$K$M$O%Q"%SUb%W%Y%[%]%_&a"&cB&eb&g&i&k&m&o'q"'sub'w'y'{'}'("(B(b((((()")b)))))*"*B*b*****+"+o+ /@`!#o'+-//3@59;=?A C@E`MOQ S@U`WY[]_a c@e`gikmoq s@u`wy{} @` @ ` @ ` @ ` @ ` ǀ ɠ @ ` ׀ ٠  @` @`!Aa   !Aa!!#A%a')+-/1!3A5a79;=?A!CAEaGIKMOQ!SAUaWY[]_a!cAeagikmoq!sAuawy{}!Aa!Aa!Aa!Aa!Aaǁɡ!Aaׁ١!Aa!Aa " B b  !"!B!b!!!!!"!""#B"%b"'")"+"-"/#1"#5b#7#9#;#=#?$A"$CB$Eb$G$I$K$M$O%Q"%SUb%W%Y%[%]%_&a"&cB&eb&g&i&k&m&o'q"'sub'w'y'{'}'("(B(b((((()")b)))))*"*B*b*****+"+o+B_STAT F LEES DIT #Q `KA387 NN.  F..  FEXCLAMS FLL F  PAWN FLL F  HEART FLL F  DIAMOND FLL F  READ ME F yCIRCLINEFLL F SPEARANKTAB F DW TAB F dDOL2 FLL F  SPSHEET DOC F #GENERAL DOC F lKOLMOG TAB F "FRIED TAB F $STAT2 DOC F %# DOLLAR FLL F ( STAT3 DOC F )mSTAT1 DOC F 17NUMBER FLL F 6 GRAPH DOC F 7~=WILCOX TAB F GCIRC FLL F I OOOOS FLL F J BSTAT PRG F K8BISHOP FLL F BSTAT RSC F DEMO BGD F 3tGR01 PI3 F 4B}GR02HORIPI3 F TB}GR03 PI3 F tB}GR04HILOPI3 F B}6666666666666p>~???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. B/STAT is being distributed as shareware. The cost for BSTAT is 30.00 (US) but the user will get a 166 page document of which 90 pages serves as a statistics tutorial. 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. B/STAT requires 1 megabyte and a double sided drive. The author can be reached on CIS # 72355,1637 or at the following address. Robert Wilson 2677 Council Ring Rd Mississauga, Ontario L5L 1S6 Canada 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 1 additional ARC files. This file contains on line help support and must be de arced as well. >>"""""">>>>"""""">> 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 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 >> "">>>> "">>-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 column in which the cursor resides. If the value is other than zero then the row is removed. In no case will the program reduce the number of rows below 1. -The decimals selections are fairly straight forward. They simply affect how the data will be displayed. If the "Global" option is checked then any action will apply to all columns. If not, then the action affects only the column in which the cursor currently resides. -The "Item" menu allows for the insertion or deletion of individual data items. This is useful if you find after typing in a whole series of data points that you forgot to enter the third one or that you entered the third one twice. It is also useful for creating lagged variables to be used elsewhere in the program. -The "Miscellaneous" section has naturally a variety of options. By selecting "Mean", "Std Dev", "Largest", "Smallest" or quartiles you will get the corresponding statistic for the variable in which the cursor resides. -The "Help" option will bring up this help file (as you can see). -The "RELABEL" option allows you to change the labels which are at the left hand side of the screen. -The remaining options allow you to move to other menus. -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 Column Y is the sum of column a and column b a+x Column Y is the sum of column a and a constant "x" a-b Column Y is column a minus column b a-x Column Y is column a minus a constant x x-a Column Y is x minus column a a*b Column Y is the product of column a and column b a*x Column Y is the product of column a and a constant "x" a/b Column Y is column a divided by column b a/x Column Y is column a divided by a constant "x" x/a Column Y is x divided by column a a^b Column Y is column a to the power of column b a^x Column Y is a to power of constant "x" ab Column Y is 1 if column a is greater than column b, otherwise it is 0 a>x Column Y is 1 if column a is less than a constant "x", otherwise it is 0 a\b Column Y is the minimum of column a and column b a\x Column Y is the minimum of a and a constant "x" a|b Column Y is the maximum of column a and column b a|x Column Y is the maximum of a and a constant "x" a!b Swaps column a and b. The column where the cursor resides is not affected unless it is in column a or b a!x Column a is set equal to the constant "x" a@x Column Y is the accumulation of the values in column a, where interest is asumed to be at "x" percent. The first payment is assumed to be at the end of the period a@b Similar to a@x, except that the percent interest rates for each period are in column b a&x Similar to a@x, except that the payments are at the start of the period a&b Similar to a@b, except that the payments are at the start of the period a$x Column Y is the present value of all remaining periods in a, taken at interest rate x%, Payments are at the end of the period a$b Similar to a$x, except that the interest rates are given in column b a#x Similar to a$x, except that payments are at the start of the period a#b Similar to a$b, except that payments are at the start of the period a%x Calculates the rate of interest, such that the present value of the values in column a equal the constant "x". Payments in a are assumed to be at the end of each period a%b Column Y is set equal to a series of rates, such that the present value of the items in a are equal to the values in b -In addition, there are commands that operate on one column only: COUNTERxx Creates a variable in column Y which has the natural numbers from 1 to xx in it deg(a) Column Y is a conversion of column a from radians to degrees rad(a) Column Y is a conversion of column a from degrees to radians mult(a) Column Y is the running product of column a rot(a) Column Y is the reverse order of column a fact(a) Column Y is the factorial of the values in a abs(a) Column Y is the absolute value of a sqr(a) Column Y is the square root of column a sin(a) Column Y is the sine of column a. Radians are assumed cos(a) Column Y is the cosine of column a tan(a) Column Y is the tangent of column a asin(a) Column Y is the arc sine of column a acos(a) Column Y is the arc cos of column a asec(a) Column Y is the arc secant of column a atn(a) Column Y is the arc tangent of column a log(a) Column Y is the natural log of column a log10(a) Column Y is the log to base 10 of column a exp(a) Column Y is "e" to the power of a exp10(a) Column Y is 10 to the power of column a int(a) Column Y is the next lower integer of a sinh(a) Column Y is the hyperbolic sine of a cosh(a) Column Y is the hyperbolic cosine of a tanh(a) Column Y is the hyperbolic tangent of a asinh(a) Column Y is the arc hyperbolic sine of a acosh(a) Column Y is the arc hyperbolic cos of a atanh(a) Column Y is the arc 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" These commands are relatively quick in execution since they are not actually parsed as a line of code would be. As you have probably noticed, they are all simple operations. B/STAT also has a general parser. If the regular commands cannot be used, the program reverts to the parser section. The parser section allows many, but not all, of the commands above. It allows certain modifiers, as well, which are not possible in the simple commands above. The mathematical operations supported are: + - plus and minus ^ exponentiation * / multiply and divide < > = logical less than greater than and equals \ minimum | maximum Three other logical operators are: OR logical or AND logical and XOR exclusive or The functions may be combined in any way. Operator hierarchy is standard algebraic. When in doubt use brackets. An example of the use of these functions might be the following: a*(( b<6) and (c>12)) This would create a variable with the same value as variable a only for the points where b is 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 blank Column Y is blanked out find(x) Searches from the current cursor position to the next occurrence of the value "x" 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 "Print to disk" option is an "on/off" toggle. When high lighted all statistical tests will print to a disk file called "BSTATPRN.DOC" rather than the printer. If the file already exists the data will be appended to the file. 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. Similarily you can restate ordinal data as nominal on occasion. 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 .272 .301 .361 20 .264 .294 .352 25 .240 .264 .320 30 .220 .242 .290 Critical Values of Kolmogorov-Smirnov Statistic No of Significance Level Points 10% 5% 1% 35 .210 .230 .270 over 35 1.22 1.36 1.63 ---- ---- ---- SQR(N) SQR(N) SQR(N) 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 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 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 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 regression. 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. -LOGIT regression is used when the dependent variable is to be constrained to a value above 0 but below 1. LOGIT setup converts unsummarized data to the form required by the regression program. (Save original data first!) -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 two 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 shows the correlation between a group of variables, rather than doing a full regression. This is often done to look at the effects of multi-colinearity 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 average requireS the same input as linear moving average. -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 lesS 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 is simple exponential smoothing. You will be asked to specify the variable to smooth, and a variable in which 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 distinct 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. -Winter's exponential smoothing is used if there is a seasonal aspect to the data (like retail sales which have a December peak). 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 with data fluctuating above and below zero. With data that go below zero, add a constant to the data to eliminate negative values. Then, after smoothing, subtract the constant. -Interpolation B/STAT uses 3 forms of estimating unavailable data. -Simple linear interpolation requires that you simply select the variable. -Lagrangian interpolation requires two variables: an "X" variable and a "Y" variable. There can be no missing "X" variables. This can be slow with a large data set, since each point is used in estimating missing data. -Cubic splines assumes that the data set in the selected variable consists of evenly-spaced observations. EXTRACT These selections allow you to reduce the size of 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 useful if you want to look at subsets in isolation. MISCELLANEOUS This menu has two procedures, in addition to the usual help selection. -Crosstabs is used to summarize data which contained in two 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 number 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 20,000 and 30,000 dollars per year. You first select the variables to use in the crosstab. If you select two, then a 2-way crosstab is done. If three, then a 3-way crosstab is done. Next, you select the break points for the classes in each variable. There may be up to 14 breakpoints, giving a maximum of 15 classes for each variable. You need only type in as many breakpoints as there are in the a specific variable, 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 value. 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 useful if you then want to perform a Chi square test, type 2, on the result to see if there are any significant relationships. -Difference is a rather simple process. The difference of a variable is simply the amount of 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. You merely supply the variable to difference and the variable into which to place the result. 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 the first representing the expected number of occurrences and the second the actual number. The test determines whether the actual data is consistant with the expected. -Chi Square 2 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 uses all data. There must be two rows and two columns. It is a test used to investigate changes in response in a pre- and post-stimulous study. See the manual for data setup. -Cochran test uses all data in the data set. There must be three or more related variables with dichotomous data. 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. """""""""""""""""""" 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 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 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. 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 18 points in each factor. The data is displayed 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 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. 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. Tic marks may be turned on or set to go in or out. 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 titles and scales used in the graph. Tic size allows the setting of major and minor tic lengths. 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 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 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. Redraw will redraw the graph if the reset graph option is off. Grids These two options turn on horizontal and vertical grids and the Z 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 draging 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 three forms of saving the screen image. The first is as a DEGAS compatable uncompressed image. The second is as a ".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 can not handle a color file so you can put out a monochrome version of the screen. The IMG files produced by BSTAT 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, Calamus and the Timeworks Desktop Publisher (TWDTP). To read the files into TWDTP you will need to select the "GEM DRAW" option in TWDTP. 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 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 clones 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 one 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. Also on the miscellaneous menu is the selection for "Legend Box". When this is selected the legend may be dragged around on the graph until you release the button. If the option has already been selected then reselecting it will result in returning to the default setting. When selected you may further move the legend by selecting "Move Legend". Reset Graph is normally set. If off then you can redisplay the graph from the previous menu simply by doing a redraw. 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<r4<NutNuNH NH,NH8NuA#H a,a>LPNuH aaLPNu pANpNpg0@|YA;AAl p"p Y Qf//  gRp mfNְcp N=@HS@M<rfdRt<eBRB|AA\ p p "X Pfb <bRAN| g kQ`2Q`"Q FgNְd/@p -Fg0g0@ nt p$X Pf d/@ $@zlxd fzoxc&_"Sp~| eEKDDRDtDD Dl|fLp/HzH .rMfCT`"{p8, g| {pNu`2p۾݆ݾZ& ܀P۬L4 fd$R$&k(*ڄNdNjRofNuHe(*NdN$&Rgp$(؁*Ne*(NdN(*Ro2(NdS(So&*NdD*RRNf$f$SB`S(l//"a R"mxNupЂmlNu,..3xhNu,.*sh'xh'xNu,.*sh'xh'x*rh%xh%xNu,.܆އ>3xshNu,.܆އ:sh7xh7xNu,.܆އ:sh7xh7x܆އ*rh%xh%xNu3X3HNu,.*rh%xh%x3HXHXNu,.܆އ܄ޅ܆އ(sh*sx<3h>3x?Fc>HHnHSGk Vf>FNuTNuHANpr,.܆އ܄ޅ܆އ(sh*sx<3h>3x?Fc>HHnHSGk00Vf >FLNuTLNu,.܆އ܄ޅ܆އ*sh'xh'x:sh7xh7xNu,.*sh'xh'x*sh'xh'xNu,.*rh%xh%x܆އ*sh'xh'x*sh'xh'xNu,.*rh%xh%x܄ޅ܄ޅ*sh'xh'x:sh7xh7xNuv" [0gt@C!(Q꒼jNuH <3Ho">3XoDFf,3XHf<3XsHL0Nug">3Xl Ff,3HXf<3HsXL0Nu>3X||F`missing Selectmissing EndselectMll - Editor Fehlermissing Wendmissing Untilmissing Loopmissing Nextmissing Whilemissing Repeatmissing Domissing Formissing Endifmissing IfExit without loopmissing ReturnProcedure in loopProcedure redefinedmissing EndfuncFunction in loopFunction redefinedmissing ProcedureLabel redefinedLocal without Procedure/FunctionLocal in loopFunction redefinedGoto into/outof For-Next, Procedure or FunctionResume in For-NextResume without ProcedureResume in Functionmissing FunctionNew VariableNew ProcedureNew FunctionNew label 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 3.0 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 3.07 U| Copyright 1986-1989|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 :&* & "$ rR V  0tb8,@&8FV n xH < $,~l (Xv"6@( ^$68j,D 4d xN ,  8"0@@PF @hvN T &@20J X0& NjL `GFA-BASIC3.Z^"*Zz>>f~@H !7 !7 !; !< !4 FFH! ! ! ! ! ! F@H ! !' ! ! ! FbH , ! N ! - !$! !! !(! !! FRH  !  !! ! !! !! FH !! FF \F0F033333FHFXGF L9FXG FFL9 B F 5ZF 5:F@16,16,254,254,144,144,254,254,18,18,254,254,16,16,0,0,16,16 4254,254,144,144,254,254,18,18,254,254,16,16,0,0 :0,0,34,34,34,34,127,127,34,34,127,127,34,34,34,34,0,0 234,34,34,34,127,127,34,34,127,127,34,34,34,34 >0,0,62,62,32,32,127,127,34,34,127,127,2,2,62,62,0,0,62,62 *32,32,127,127,34,34,127,127,2,2,62,62 >0,0,3,128,7,192,15,128,15,32,14,96,15,224,15,224,7,192,3 .128,3,128,3,128,3,128,7,192,15,224,31,240 P0,0,3,192,7,224,7,224,15,240,31,248,31,248,15,240,3,192,3,192,3,192,3,192,7 224,15,240,31,248,63,252 2F0,0,28,112,62,248,126,252,255,254,255,254,255,254,255,254,127,252 .63,248,31,240,15,224,7,192,3,128,1,0,0,0 ,FF 4FF 4FF 4FF 4FF8F48F48F48F48F48F48 F48 F48 F48 F48 F48F48F48F4<F8F48F48F48F48F48V F8k F,8u! F0F0\(F0\(F8F0FXF8F8FP9wF.P9V!!  F,.P9V!!  F,P9FXGF(P9V!!  F :F F8F8F8F&833333߀F8ߠF8 F8!F8"F8#F0F8$F8%F8&F8'F8(F8)F8*F8+F8,F8-F8.F8/F80F81F82F83F84F85F86F87F 88FF =F"4DOES NOT WORK IN LOW RESFFFDlFDF$F =T߀FN!fF!F$FXG FN  F =nFGBJAN ,FEB ,MAR ,APR ,MAY ,JUN ,JUL ,AUG ,SEP ,OCT ,NOV ,"DEC " 89 F =߀F,89F$F 4FF8W F4 F 4B߂ :\F 4FF4FXGF:L9; VAR ݀  ! F >rF ,,!!!!!F 8:b F"8г!!!;!F28?#G ߖ ٙF ^r?ߘF4 Not enough memoryFFF lF XGFeL! F ^RFFF$FH! F, F4LY! "Choose maximum number of pointsF,LY! "Highest allowed is "7?F>LY! "(To leave at this you need not enter dataFF _h?ݳFa<LY! "Maximum to use GDOS is "7?ݪFF$F LY! " New Value: FH!9݌FaH!9FuH!9ߠFuH!9߀FuH!9߀FuH!9?F8@F 8AF `AF"8w! ! F8?u!? F$FFF F8Bw?! F4H?!>݀ !B! !?߀ F4 !ߠF8CF0G F8DFF ah$F8DF 033333#ߒ| FF$FF3F3<F 4FF, FFF\FFbF 8EFFFFFF ( FF8FFF aF bBC߀F|o F$FlF blD߀F|F$FXGF|L! F bFFFF0г! !!F4too large a fileFFFt 8JLFF 8NMFF 8o,FF4 !ߠFXGJFaM!F L9F mVF85F mJ?FXJG?FaL9 F mF$FXGNFaM!F L9F mFXGN݀FaM! F n.F nN>FXNG>Fa2L9; VAR ݀  ! 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FF \F0#J! 3! 3! 3! 3 F \FJ r F 4 incorrect data FFF 8Fi4 CON:FFFFFC$FFF ! ! ! FFF ! FFBPM" "'1 Way Analysis of Variance Latin SquareF PMcF^PM"LSource Of Variation Degrees of Freedom Mean Square F-Value PercentF PMcFXGFc 4FF8 FP9Fc # ! F4 FP9FF # ! F4 F FO # ! F 4F # ! F 4F$F F*PM"Due Rows F$F ߀Fw*PM"Due Columns F$F T߀Fl*PM"Due Treatments F$F Fe*PM"Due Residuals F$F F PMcF 0McFP9 FDF Q߀FsFF$FFF.A!!Q!@!!u!!!!!!!!F8QF!8@F!FF.T!!1 WAY NESTED ANOVAF *LY! "number of treatmentsFFH!9ߠF H!9ߠF H!9߀F H!9߀F H!9F 8AF *AFFF \F8! F00#J!N!!u!!!!!!!! FF \FJ FN4 incorrect data FFF 8$FiFF4 CON:FF # FF$F$FFFF  F FF PMcFFDPM" "(1 Way Analysis of Variance Nested DesignFF PMcF^PM"LSource Of Variation Degrees of Freedom Mean Square F-Value PercentF PMcF 4FF8 FP9Fu #! F4 FP9FF #! F4 F #u! F 4F #! F 4F*PM"Between Treatments F 4FF8 FP9Ft #! F4 FP9FF #! F4 F #! F 4F #! F 4F*PM"Among Samples F 4FFP9Fo #! F4 FP9FF #! F 4F*PM"Residual F PMcF 0McFP9 FRF Q߀FaF # F$FFF ! ! ! ! F6H  ! ! ! !  FA!@!F8AF 8F8@FFF&T!! 2 WAY ANOVAF0LY! "number of treatment levelsFF0LY! " for Factor A FFH!9߬FcH!9FcH!9߀FcH!9߀FcH!9F 8AFFF \FP 9! F8F 8$FFF4T!!Variable containing DataF *##!!!3!@!3!3 FaP 9 FP9 FFF <@F!8T!!Variable Containing A LevelsFo*##!!!3!@!3!3 F P 9 FP9 FFF$F @F!8T!!Variable containing B LevelsFo*##!!!3!@!3!3 F FF$F @FP 9 FP9 F8F8QF HN>FNF8QF$F6T!!Variable to store residualsF*##!!!3!@!3!3 FiP 9 FL  9 RESIDUALSF!. Q߀ #N݀ FNF$F$F$FFF A@F \F8OFF(8#!J!N! 3!3!3!3! 3 F \F  FJ4 incorrect data FFF 8FiFF4 CON:FFFF$F$F|FFF ! ! ! ! FFFF ! FF6PM" "2 Way Analysis of VarianceFF PMcF^PM"LSource Of Variation Degrees of Freedom Mean Square F-Value PercentF PMcFXGFc 4FF8 FP9Fc # ! F4 FP9FF # ! F4 F FO # ! F 4F # ! F 4F$F .F*PM"Due A F$F t߀F *PM"Due B F$F ʺ߀F *PM"Due AB F$F F *PM"Due Residuals F$F  F PMcF 0McFP9 FDF jQ߀FsFFF$FFF ! ! ! ! F6H  ! ! ! !  FA!@!F8AF .8F8@FFF&T!! 2 WAY ANOVAF0LY! "number of treatment levelsFF0LY! " for Factor A FFH!9߬FcH!9FcH!9߀FcH!9߀FcH!9F0LY! "number of treatment levelsFF0LY! " for Factor B FFH!9߬FcH!9ߠFcH!9߀FcH!9߀FcH!9F8QFF 8AFb ξ! ! ! ! F8QF4 data not entered FFF $F  QAFFF \FP 9! FP 9! F8F 8FFF4T!!Variable containing DataF!*##!!!3!@!3!3 FaP 9 FP9 FFF F@F!8T!!Variable Containing A LevelsF*##!!!3!@!3!3 F $FP 9 FP9 FFF @F!8T!!Variable containing B LevelsF*##!!!3!@!3!3 F FF$FP 9 FP9 FFF Ѳ@F!8T!!Variable containing C LevelsF*##!!!3!@!3!3 F FF$FP 9 FP9 F8F8QF @F! :N>FNF8QF$F6T!!Variable to store residualsF*##!!!3!@!3!3 FiP 9 FL  9 RESIDUALSF!.  Q߀ #N݀ FNF$F$F$FFF A@F \F8OFF(8#!J!N! 3!3!3!3! 3 F \F  FJ4 incorrect data FFF 8FiFF4 CON:FFFF$F$F|FFF ! ! ! ! FFFF ! FF6PM" "3 Way Analysis of VarianceFF PMcF^PM"LSource Of Variation Degrees of Freedom Mean Square F-Value PercentF PMcFXGFc 4FF8 FP9Fc # ! F4 FP9FF # ! F4 F FO # ! F 4F # ! F 4F$F  F*PM"Due A F$F f߀F *PM"Due B F$F ֬߀F *PM"Due C F$F F *PM"Due AB F$F 8߀F *PM"Due AC F$F ~ߠF *PM"Due BC F$F F *PM"Due ABC F$F  FC*PM"Due Residuals F$F F PMcF 0McFP9 FDF tQ߀FsFFF$FFFF(4 severe error of unknown type FFF  O߀FfF$F OFfF$FF ()#S!!2 3!#3!$3!%3 FF Q!R!!!!!|!!FF !& !' !( !) !* FFH& !  !' !(! !) !* F8|F 4$ !F 4% !F8,F (8*#S!! 3!(3!*3!)3!|! FF8+#(3!#3! F R# F3& ! !' !( !) !* FD#߀ F$FXG݀F! ږ(! FH(!9F$FH$9(! FH%9$ FH 9N(! F tFXG݀F!XG݀F! N  FH#!9#!   F 8fFH#!9F$F "F FXGS݀F& ܦ##!߀! 3 FXG݀F H'9FXRG݀F0! R F0#)R *R FFH'9' #R! F  RF FXG݀F H!  9' F ܄F 8FXG݀F H!  9ߠF F$F ۠F& ! !' !( !) !* FD# F,F&(*#S!!2 3!+3!*3!)3!! F&Q!!R!!!!|!!!!F8|F! 4) !F 4* !FXGS݀F0F #  F0! F$FH B#߀#!߀! 3 ## #  Fa|F# 8FXG݀F 8  F0! FFH)9) F # FH*9* F$F hF$F ݺF ##S| FD#߀ F$FXG݀FH)9) #S| F$H*9* #S| ) ) F# ߞ* FH*9߀F $FH*9N* F  #  FH*9߀F$F >F 4+ !FXRGS݀F0F L#  F0R! F$F< b##R!߀! 3 ##  FXG݀F 8 F0R! FF0#) * FFXG݀F! 8  F0R! FF0#) * FFH+!9+! F F F$F RF #  F 8|F| 8F|XG݀F #+! ݩ:ǘf FH+!9݀F$FXG݀FF J#+! ݩ:ǘf FH+!9݀F$F*H+!9+! 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F  F0FXGd݀F!03 FF #3  FH39߀N3 F! 8F8QF$F bFF #Q݀ F/ !" !0 !1 !2 !3 FD#߀ F$FXGd݀F!XGd݀F!H"!9FXGd݀F!.H"!9"! .! 3 .! F vF LF 0FXGd݀FXGd݀FH.!9FXGd݀F(H.!9.! 0! "! F *F F FXGS݀FXGd݀FH-!9FXGd݀F(H-!9-! ! .! F F F F 0FF 0FF0(߀ F  F#3!-3!33!13!S!d FXGS݀FFXGd݀FFH-!9-! / F F F/ !" !0 !1 !2 !3 FD# F,F23!-3!33!13!S!d F!!!R!FU!!!!!FXGd݀FFXGd݀FFH!9FXGS݀FF(H!9! -! -! F FH!9! F FH19߀F rF0F0F8F,## #݉p_A6 F FF0¸FXGd݀F H39FXGd݀FH393 ! 1 F F03 1 FF F0w! FF 0N FF 0FF 0FF0(߀ FXGd݀FFH193 F F VFXGS݀FF H39FXGd݀FFH393 -! 1 F F FXGS݀FFXGd݀FF0UF 3 F0U߀F$F 1 F 0UUF$FH-!9-! UF ~F bFF((/#S!!2 3!+3!43!53!! F ,& !6 !7 !8 !) !* !9 !: !3 ! FjH& !7 !8 !) !* !9! !: !3! ! FH6! F4!!!!Q!|!!!!R!d!!!!F h# F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F 4 !F 8 F8QFXGS݀F90! F 8FF ## # F8QF 8 F  F$F FF8RF #Q݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXGF) #  F 8RFF$F F #R F ,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F8R߀FXG߀F9 h F8QFF$F JFF #Q݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$F 8F8TFF(8*#S!! 3!43!83!73!|! FF `#| F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXGS݀F9XG݀F9 8  F0! FFH!9#7 8 F3 F# F# 43 !FXG߀F3(8*#S!! 3!+3!*3!)3!|! FF0NS| F #݀ F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXG݀F9H9!9) 8 7 FXRG݀FFH3!R93!R +!R F RF F FXG݀FFXG݀FFH4!94! 3! F vF ZF8,#33!+3! F  F,6 !& !7 !8 !) !* !9 !: !3 ! FD#߀ F$FXG݀F9XG݀F90FXRG݀F90+!R 4R! FF nRFH3!9F4H6!9F4 JF .F#!33!+3 FFXG݀FH3!9+! F :+! FH3!9F$F F8F0F \߀IF #3!  F 0#3! FH5!9FFF$F F8u!߀ FXG݀F H5!93! F &F #!!&3!63!33!53 FFXG݀F H+!9F0ĸFXG݀F 0H+!݀94! 8 8 F00+!߀ +!݀ F F 0N FFXG݀F+.H+!݀9+!߀ F6H+!9+! +!݀ 7 F PF F*0#S# ݀ FXG߀F"H5!905! F&H5!9߀5! F*H5!9# #߀ F85! F#5! ! FH5!9)F FXG߀FXG߀F0+! FXRG݀F&0+!R߀ 9!R F 2RFH4!9F F FXGS݀F9XG݀F9 8  F0! FFH!98 7 F F F 8F,6 !& !7 !8 !) !* !9 !: !3 ! FD# F,FS!!2 3!;3!3!3 F FH F !!!!!!!R!dF 4 !FXGS݀FdP9FP9FP9FXG݀Fd 8  F0! FFXdG ߀F #;d! F  F$F ddF *F$8  F48#  F8 F! F! F! F8 F! F! F! F F! FF2(0#S!!!2 3!<3!#3!$3!%3!!! F & ! !+ !' !( !) !* FVH& !  !+! !' !(! !) !* F Q!R!!!!!|!!F!!!!F!8|F!0F!4 ## ## # F !+ !' !( !) !* FD#߀ F$FXG݀F#H 9߀F H$9F H%9F F8,F(8*#S!! 3!+3!*3!)3!|! FF ,ߣ =pF!XG݀F)XG݀F)H(!9+! F) F F8+#(3!#3! F N# F3 & ! !+ !' !( !) !* FD#߀ F$FXG݀F*H$9(! FH%9$ F pFXG݀FF H<9FXG݀FF(H<9< #! #! $ FF FH<9u< ! FH 9+! F F0FXG݀F  #( <  F0( < F$F  # FH+!9< F$F  F 0FF  # F0øF$F |F  # ߀ FXG݀FXG݀F"H#!9#! Nw$ ! FF  |F  `F$F  # F & ! !+ !' !( !) !* FD# F$F  #߀ F8FF 8.##3!+3!(3!!! FXG݀F0FXG݀F0+! +! FF  F H$9FH%9FF  dF$F  #߀ F8F  FXG݀FFXG݀FF H#!9#! #$ F  TF  8F$F 8.##3!+3!(3!!! F"#+3!!!#3!(3!$3! FF$FXG݀FH%9$ FXG݀FFH#!9+! FF  .F  F & ! !+ !' !( !) !* FD# F,F"2#3!!d!3!43!$3! FF!!!!RF! "# FXGd݀F*H$9$ #߀ FF  F$FXGd݀FXGd݀F0FXRGd݀F"04R! 4R! $R FF RFRH!9F4 `F DFXGd݀FH$9N! F FXGd݀F0FXG݀FH#!9#! $ FF0#! #! FF VF H$9F 2F= FFF@FFFJT!!.Linear Interpolation: Variable containing DataF *##!!!3!@!3!3 F FF @F \F#J! F \F$FFF!@!MFFF@T!!$Difference: Variable containing DataFi*##!!!3!@!3!3 FcFF "@F8 F 8MNFF zNFNF$F@T!!$Difference: Variable to place resultFi*##!!!3!@!3!3 FtFF"  #N݀ F 8NMFF$F$F b@F \F#J!! F$F \FF  FA!!@!MFFFBT!!'Moving Average Variable containing DataF*##!!!3!@!3!3 FlFF @F8 F 8MNFF ZNFNF$FBT!!'Moving Average Variable to place resultF*##!!!3!@!3!3 FlFF"  #N݀ F 8NMFF$F$F @F.LY! "Period of Moving AverageFFLY! "Period: FFH!9FdH!9߀F H!9F H!9߀F H!9F8@F 8AFFF AF8! F Z߀FF4 Improper dataFFI 8Fm \Fr(8@#J! ! !! F  @ F4 improper dataFFi$F$F$F$F \FrFFA!!@!MFFFFT!!+Fourier Smoothing: Variable containing DataF*##!!!3!@!3!3 FrFF ~@F8 F 8MNFF NFNF$FFT!!+Fourier Smoothing: Variable to place resultF*##!!!3!@!3!3 FrFF" x #N݀ F 8NMFF$F$F f@F&LY! "Fourier SmoothingF2LY ! "Terms of expansion to keep: FFH!9ݠF H!9߀FfH!9FfH!9߀FfH!9F8@F 8AF `AFFF8! F$ ߀Fn4 Improper dataFFI 8ZFm \Fr$8@"#J! ! ! F T@ F4 improper dataFFi$F$F$F$F \FrFFA!!!!!!@!MFFFRTh!!6Simple Exponential Smoothing: Variable containing DataF*##!!!3!@!3!3 FoFF8 F 2@F 8MNFF xNFNF$FRTh!!6Simple Exponential Smoothing: Variable to place resultF*##!!!3!@!3!3 FoFF" , #N݀ F 8NMFF$F$F j@F2LY! "Simple Exponential SmoothingFF,LY ! "Smoothing Coefficient: FH!9ݠFhH!9߀FnH!9ߠFnH!9߀FnH!9F0LY ! "Estimate of initial level: FH!9ߠFoH!9ߠFoH!9߀FoH!9FH!9F8@F 8AFFF dAF0! F VFo4 Improper dataFFI 8^Fm4 F I B F0F 8F 05 FF$F \FF.8@#J! ! !!!! F   @ F4 improper dataFFi$FFF \Fr4 CON:FF #!! FFFF$F$F$F \FF !! F FF!>PM" ""Browns 1 Way Exponential SmoothingFF PMcF PMcF8 FP9F #! F4PM" Smoothing coefficient : "F8F #! F PMcF4PM" Standard error of estimate : "FP9 F  #! Fd PMcF4PM" Projection for next period : "F 0McFF  nQ߀FeF #!! FF$FFF FH FA!!!!!@!MFrFFRTh!!6Double Exponential Smoothing: Variable containing DataF*##!!!3!@!3!3 FoFF "B@F8 F 8MNFF !NFNF$FRTh!!6Double Exponential Smoothing: Variable to place resultF*##!!!3!@!3!3 FoFF" "< #N݀ F 8NMFF$F$F $h@F2LY! "Double Exponential SmoothingFF,LY ! "Smoothing Coefficient: FH!9ݐFhH!9߀FnH!9ߠFnH!9߀FnH!9F8@F 8AFFF $bAF0! F #F 4 Improper dataFFI 8$\Fm \Fr,8@ #J! ! !!!3 F  $@ F4 improper dataFFi$FFF \Fr4 CON:FF #!!3 FFF$F$F$F \F FF !!23 F ! F2F>PM" "#Brown's 2 Way Exponential SmoothingF PMcF PMcF8 FP9F #! F4PM" Smoothing coefficient : "F8F #! F PMcF4PM" Standard error of estimate : "FP9 F XGFa # ! F PMcF FPM" Projection for ߀  periods on : "F %F 0McFF &Q߀FeF #!!3 F$FFF FH FA!!!!!!@!MFFFRTh!!6Holt's Exponential Smoothing: Variable containing DataF*##!!!3!@!3!3 FoFF (@F8 F 8MNFF 'NFNF$FRTh!!6Holt's Exponential Smoothing: Variable to place resultF*##!!!3!@!3!3 FoFF" (~ #N݀ F 8NMFF$F$F +@FF2LY! "Double Exponential SmoothingFF6LY ! "!Smoothing Coefficient for level: FH!9ݸFhH!9߀FnH!9ߠFnH!9߀FnH!9F6LY ! "!Smoothing Coefficient for trend: FH!9ݸFnH!9ߠF H!9ߠF H!9߀F H!9F8@F 8AFFFL (A߀#! !  F +AF0! F0! F. +8  ߀F4 Improper dataFFI 8+Fm \Fr.8@!#J! ! !!!!3 F +@ F4 improper dataFFi$FFF \Fr4 CON:FF #!!!3 FFFF$F$F$F \F FFFF !!!23 FF ! FF>PM" ""Holt's 2 Way Exponential SmoothingFF PMcF PMcF8 FP9F #! F8PM"# Smoothing coefficient for level: "F #! F PMcF8PM"# Smoothing coefficient for trend: "F8F #! F PMcF4PM" Standard error of estimate : "FP9 F XGFa # ! F PMcF FPM" Projection for ߀  periods on : "F -F 0McFF .Q߀FeF #!!!3 FF$FFF FH F(!A!L!s!!!!!!!@!MFFFTT`!!8Winter's Exponential Smoothing: Variable containing DataF *##!!!3!@!3!3 FSFF 0@F8 F 8MNFF /NFNF$FTT`!!8Winter's Exponential Smoothing: Variable to place resultF *##!!!3!@!3!3 FSFF" 0 #N݀ F 8NMFF$F$F 7@F4LY! "Winter's Exponential SmoothingFF6LY ! "!Smoothing Coefficient for level: FH!9ݸFhH!9߀FnH!9ߠFnH!9߀FnH!9F6LY ! "!Smoothing Coefficient for trend: FH!9ݸFnH!9F H!9ߠF H!9߀F H!9F<LY ! "'Smoothing Coefficient for seasonality: FH!9FnH!9߀F H!9ߠF H!9߀F H!9F0LY ! "Initial estimate of level: FH!9ݠF H!9ߠFsH!9߀FsH!9FH!9F0LY ! "Initial estimate of trend: FH!9ݠF H!9FsH!9߀FsH!9FH!9F(LY! "Period of Season: FFH!9ݠFoH!9F H!9F H!9߀F H!9F8@F 8AFFF 7AF0! F0! F0! F8! F4 F 5I B F0sF 86F 0s5 FF$F4 F 6JI B F0LF 86`F 0L5 FF$FN 6߀߀݀F 4 Improper dataFFI 87Fm \Fr80%#J! ! !!L!s!!!!3 F  7LF4 Improper dataFFI$FFF \Fr4 CON:FF #!!!!3 FFF$F$F$F \F FFFF !!!!23 F ! FF:PM" "Winter's Exponential SmoothingFF PMcF8 FP9F #! F<PM"' Smoothing coefficient for level: "F #! F PMcF>PM"( Smoothing coefficient for trend: "FF PMcF<PM"' Smoothing coefficient for seasonality:"F8F #! F PMcF4PM" Standard error of estimate : "FP9 F PMcFXGFa # ! F FPM" Projection for ߀  periods on : "F 9F 0McFF :Q߀FeF #!!!!3 F$FFF ! !; F.H! !; ! ! FR!d!!!@!!A!FFFP9F!6T!!Cross Tabs Select VariablesF*##!!!3!!3!3 FiFF BF8AF8FFFF&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 <4F8@F 8AFFF8FF 4 F8F >I B FP9݀FFH;!95 F8F$FF$ >V߀F F ;A߀F BAF \F#J!!3!;3!3!3 F \F8RF3F4 CON:FFFF #!R!;3!3!3!3 FRF ?pR F&8d w߀! FaFF Bd?F@LY! !+Warning a yes answer destroys existing dataFH!# Put summary data| in data editor? !! YES | NO !@FF B@߀Fr8dF8FFXG F"XRG Ft.Hd!R9߀݀!R F @RFdF @FF @ F AN FXGJ݀FX GN߀FH!9ߠF AF AF$F&8d w߀! F BzJdFXdGJFXGN݀FH!9ߠF BHF B,F$F 8JdFF8N F$F$F$F$FFF !; ! FF !R!2;3!3!3!3 Fd!S!!F4####FF C6 FF4#####F$F Cj FF4######FF$F C FF4#######F$F C FF4########FF$FF#ZPM"& Cross Tab of   vs  FF D F\PM"' for level R߀  of  FF$F PMcFHPM"  " FFPM" "FFXdG FPMc!!7d"F E6dFPMc! Total F PMcFXG F PMc! ####!7"FFXdG F2PMc!!7߀߀R!d "FF EdF PMcF EFPMc! Total "FXdG F<PMc!!7#R߀ !d "F FLdF PMcF( G"R#  RF PMc! Grand Total"FXdG FPMc!!7!d "F FdF$F 0McFF GxQ߀FF #!R!;3!3!3!3 F$FFF @!FFFPTp!!4Cubic Spline Interpolation: Variable containing DataF*##!!!3!@!3!3 FaFF H@F \F8&#J! F \FJ H F 4 not appropriate data FFF $F$FFFFF !@!MFrFFPTl!!5Lagrangian Interpolation: Variable containing X DataF*##!!!3!@!3!3 FiFF J@F8 FPTl!!5Lagrangian Interpolation: Variable containing Y DataF*##!!!3!@!3!3 FiFF J~@F \F"8@##J! ! F \FJ Jx@ F 4 not appropriate data FFF $F$F$FFFFF ,d!! !# !$ !% F2H> !#! !$ !% F \F480#J!!!3!>3!#3!$3!%3!!! F \FJ TZF!XGFXGF!H#!9ߠF T<FH#!9ߠF$F SF SF$F8FF8u! F4 CON:FFFF#!!>3!$3!%3 F 8F TtF!4޾ FACTOR LOADING VARIABLES FF\4P F8Rw! F8dw! F 8FF 8dFF*"#!#3!3!3!3!d!R!! FFF 8V~F F$F 8VF F$F  ! ! !> !# !$ !% FHB! FFFF XF$TP!! ROTATION F(T!! F XF WrF&T!! NONE F$F WF!&T!! VARIMAX F$F WF!&T!! QUARTIMAX F$F X>F!&T!! EQUIMAX F$F XF!&T!! ORTHOBLIQUEF$F XF*T(!!COMMUNALITIES F T!! FA XF YFT!!NO F 8Y>FT!!YESF$F XF0T(!ߐ!# FACTORS TO EXTRACT F T!ߐ! FO XF 4 F YB ݀F4 FF$FT!ߐ!F XFF!!2>3!$3!%3 F R! F2F,PM" "Factor Analysis FF PMcFNPM"< Factor # Eigen Value Percent Variation EstimatedFPPM"= Covered CommunalityFFXRGFPMc!#####!7R"F6PMc!############.####!7$R߀ "FF:PMc!#################.##!7%R݀ "FF6PMc!############.####!7>R߀ "FF PMcF [(RF 0McFF \NQ߀F#F#!!>3!$3!%3 F$FFF,d!!H ! ! !#! !$N !%N FFF0F4F@T!!%Principle Components Select VariablesF(##N!!!3!!3!3 FsFF aVFJ!$ Destructive Process | Continue? !! YES | NO !@Fl aP@߀Fv \F"8)#J!!3!#3!$3!%3 FFXG݀F%6L9; FACTOR ݀  ! FL9 FP9FF ^,F _:FXGFL9 FL9 FXGFH#!9ߠFH#!9ߠF ^F ^F$F \F8FF8u! F4 CON:FFFF#!!$3!%3 F 8F _`F4޾ PRINCIPLE COMPONENTS FF\4P F8Rw! F8dw! F 8FF 8dFF*"#!#3!3!3!3!d!R!! FFF$F$F ! ! !# !$ !% FHB! FF!!2$3!%3 F R! F2F0PM" "Principle ComponentsFF PMcF@PM"- Factor # Eigen Value Percent VariationFF:PM"( CoveredFXRGFPMc!#####!7R"F6PMc!############.####!7$R߀ "FF:PMc!#################.##!7%R݀ "FF PMcF b~RF 0McFF cjQ߀F#F#!!$3!%3 F$FFF&d!!@!!!!!R!!F  ! ! ! !? !4 !5 FRH ! ! !?! !4! !5! F4 !݀FFF0F4F 8Ru!N݀ FNTx!!2Discriminant Analysis Select Independent VariablesF(##R!!!3!!3!3 FiFF eZFJT!!/Discriminant Analysis Select Dependent VariableF&##!!!3!@!3!3 FFF$F m(F!P9 FXG݀FL߀9 F4L9; FUNCT ݀  ! F eF L9 CONSTANT FL߀9 FXGFL9 FL߀9 F f<F \F*8/#J!!3!?3!43!53!! FF f F4 improper data FF 8m"Fi g4߀F!XG߀FL9 F gF$F gFXGFXGFH?!9ߠFH4!9ߠF gxF gdF$F h@FX߀GFXGFH?!9ߠF hF gF$F hFXGFXGFH4!9ߠF hF hpF$F \F8FF8u! F4 CON:FFFF#!!53 F 8F hF 4޾ FUNCTION COEFFICIENTS FF\4P F8Rw!ߘ F 8dw! F 8FF 8dFF*"#!?3!3!3!3!d!R!! FFFXG߀F:L9; CLASS ݀  ! F jF  kFXGFL9 F kbF$F4޽ AVERAGE SCORES F\4P F8Rw! F 8dw߀! F 8FF 8dFF*"#!43!3!3!3!d!R!! FFF$F$FFF ! ! !4 !5 !? FHB! FF!!253 F R! F2F0PM" "Discriminant AnalysisF PMcFPPM">Function Eigen Wilke's Bartlett's Degrees PercentFPPM"= # Value Lambda Approx of ChanceFFHPM"6 Chi Square Freedom FXRGFPMc!####!7R"FF8PMc! #########.###!75R߀! "FF6PMc! ######.###!75R݀! "FF8PMc! #########.##!75R݀! "FF6PMc! ##########!75R݀! "FF6PMc! ########.##!75R߀! "FF PMcF nRF 0McFF pJQ߀F#F#!!53 F$FFFd!|!!!!RF ! ! !# !* !) F4H ! !#! !*N !)N F4 !݀FFF0F4F@T!!%Correlation Analysis Select VariablesF(##N!!!3!!3!3 FsFF tdFXG݀F!L9 F qF qFXGFL9 F qF$F \F8R,F (8*#J!!3!#3!*3!)3!|!R FF rF!XGFXGF!H#!9ߠFH#!9ߠF rdF rPF$F \F8F4޾ CORRELATION MATRIX FF\4P F8Rw! F8dw! F 8FF 8dFF*"#!#3!3!3!3!d!R!! FFF$F ! !# !* !) FHB! FF6!2 3!!@3!*3!)3!43!3!3!S!! FF2!!"!!!!R!d!!!!!![!F XGF uJ#* ߫pǝ F H)9F H*9߀F$F uF 4@ !F 4 !FXGF H9F H49FH@!9݀FF uF0EFH߀9FFH4߀9FF 8F v# FF#$FXGSF0F v|# ߀ F0(! ߀ F$F8F v# F 8#߀!! 3 F $F$ z4###!! 3  F! 8!F w F !FF$FXG!߀F 8"F" wj##  # F"FF$F8R " FF0!R FF w# F 0߀!R F $F0#)" *" FF" x## # ߀ F!0F $FH9 N FXG!߀F 8"F" x##  # F"FF$F8 " FF0[! FF x# F 0[[߀! F $F0[#[)" *" FF" y(##  # F0[F$FH!9! [F xLF0! F y# F "0߀! F$F0#) * FFH494 F y# F0EEN FF$FH!!94 FF w6F9H4!94! F$F v4FF(1#23!,3!! F "!!!!!!!![!F!0F8FXG݀F! 8FF0 F 8!FXGF! {0(!  F 8!F0 (! FF$F zF 8!F {|#(! ݫpǝ FD#߀ F 8}>F {#  F0FpXGF! !! F,! !,! F {F!$F0! F0[! FXGFH!9[! FH,!9,! [F |6FXG݀FF },#  F0[! F }&#[ FFXGF"H!9! [! F"H,!9,! [,! F |F$F$F |F$F zF 0( FF D# FF,F2(2#!S!!2#! 3!53!+3!A3!! !@3 F,!!Q!!!!|!!!R!!!F (E!!!!![!k!-!!4!8!F ~# ߀ F0ʸF$F0θF ~T# F0߀F0ʸF$F ~x# F8 F$F ~#݀ F8 F$F8FXGF H)9F H*9F ~F 8F # FFF$F0 F ># F0 F$FXGS߀F8F # F 8#߀!! 3 F $F4 ###!! 3 ߀ F |F# 8jF#XGF 8  F0! FF F# F 0߀! F $FH)9) F F$F `F 8#|F| ##S| FD#߀ F$FXGFH)9) #S| F H5߀!9) F FXGS߀F8F ^F 8#߀!! 3 F $F #!! 3 FXGF 8  F0! FF FF 0߀! F $F&H*9* #) #) F F$F "FXGF X* FH*9N* F 8nFN H*9F$F(H5߀!9* NS| F # F H)9F$F 6FH5!9F6#! 3!!@3!*3!)3!43!3!3!S!! FF 6# ߀ FF#$FXG݀F!XGF*H+!9!   #S| FFD0[#!   #S| #!   #S| F #[ FH+!9+! N[ F$F ,#[ F!H+!9F$F # F&H+!9!  E#S| F<0[#!   #S| #4 EE#S| FF #[ FH+!9F 8FH+!9+! N[ F$F$F FH+!9݀FF$F hF XF0FXGF0(! ߀ F VF  ߃nPFFXG݀FFXGFH!9+! FF F F$F L# F!XG݀FFH!9! F (F$F81#3!@3!! F & ݫpǝF#D#߀ F$FHA 9FF< ##  #߀ ߀wf F 00 FFN0߀#S|#ݠ  F$8#߀ F>#! F prob of not significant mullticollinearity */ HA 9)F 8FHA 9ߠF$F # ߀ FH5!9) F $F0kF 8!F T F !FF$F0*! FFXG݀Fi 8RFF # ߀ FRF#$F,H5߀!9R! * Fn .#  F>H5!95! 5߀! ) F$F F! # ߀ F$H5!9! FF$FHA 9F #X:S F2H5!95! #߀ F 8FH5!9F$F H5!9ߠFHA9F0F0ϸF8 ߀ F#!53!S!! 3! FF8QF0F 8F # FSF#$F8FXGSF #!  F0-! ! FF J# F"0--߀! F$FHA 9A --F # ߀ F&0--! ߀ F $F #Q FHA9A --F0-[FF0[[FF$F 0[-FF8QFF$F FF0F  #A F-,0#A  A FHA 9A F #A #-- F"HA 9#A -- F$F$FHA9F ,# ߀ FHA 9F$F 8!F \ FF!FF$F0-4! EE#S| FF&HA9-* * A F0[A F8S|߀F # ߀ FF#$F0F04F J#- F 0A -* * F $F z# F04([* * F$FXG݀F 8FF # ߀ FF#$F0k* * F*H5߀!9kN4@! F # F0FXRG݀F0@!R @!R FF <RF2H5߀!9kN4#@!  F$F F # ߀ F.H5!9* N4@! FF$F #݀ F0F$FHA9* N4 FHA9F80# #S|݀ F HA9FHA9F #A vȴ: F8HA9#A  ##݀A  F $F >#A  FHA9F$FHA9F z#A  FHA9F$FHA9FHA9F #A F#A !! F$FHA9)F #݀ F"H5!9! FXG݀FHH5!95! 5߀! ! F BF!$F0ҸF # F#!53!S!! 3! FF$F8 ߀ F # FHA 9F0F(XGS݀F0-! ! FF0-! ! FF00߀! ݀! FHA 9A -F0FF >F$F # F HA 9A F$FXGS߀F>H!  9!  ! FF 0F8!F&0 #S!  !R!! FHA 9RFHA 9FXGS߀F>H!  9!  ! FF F0FXGFB05! *߀ 5! *߀ F LFHA9F # F(HA9A A F!$F  A FHA9ߠF$F 8!F P F!FF$FXG!߀FXG!߀F 0* F 0* F L# ߀ F # F0F 8F0*߀ F$F &F0F 8FF0*߀ F$F$FH@!9@! F F rF  F0F H5!9#S| FXGFXH5!95! 5! 5! @߀!݀ F  ߀FXG݀FdH5!95! 5! 5! @߀!݀ F ^F!$F F!0H5!9A N(5! F$FH5!9߀F( D# F,F2(3#!S!2$!#! 3!53!3!A3!!!@3 F<!!%!!Q!!!&!'!(!|!!!R!!!F !!!!![!EF! # F 0FF$F 8$F8FFXGF H)9F H*9FP9  F F 4B !F 4C !F8|FXGS߀F$ #߀#!! 3 F!|F# 8FXGF 8  F0! FFH)9) F F$F F >##S| FD#߀ F$FXGFH)9) #S| F H5߀!9) F! TFXGS߀F "#!! 3 F!XGF 8  F0! ) FFH*9* F! F$F FXGF f* FH*9N* F! 8|FN H*9F$F(H5߀!9* NS| F! DFH5!9F0ոF8!F6#! 3!!@3!*3!)3!43!3!3!S!!! FFXG݀F!XGFHB!9! F!0[! ! F #[ FHB!9B! N[ F$F # FHB!9݀FF$F #[ FHB!9F$F x# FHB!9! F!0[! 4 FF N#[ F4HB!9F 8rFHB!9B! N[ F$F$F DF 4FXG݀F!HB!9B! F! FHB!9݀F!XG݀F!&HB!݀9݀F&HB߀!9F! F8&F8F&X%G߀݀F0ָF8(FXG݀F"0B! B! B! FF8QF8F^#& F F#  F 8QF$FF F ##Q # F! 0FF 8(F$F F #& FP9(F&FF 8F0F" 4##B!  ֿz F.0#S|& #B!  F$F.#!&!S|߀& F 0)FF # FP&9(F&FF 8F98F$F$F#߀ F 8!݀F#C3!B3!(!! F#C3!B3!$ F 8'&F f#&߀ F$#B3!C3!3!&!S!!!| F$F#' F! %FFXG&߀F 8 FP 9 F FP &9 F&P &݀9  F 8$&F D# F&,F23!-3!$ F !FXG߀$FXG߀$FH-!9! F tF XFF2-3!3!)! FF !FXG݀F"H-)!9)! )!) F F9XG݀FXG݀F # ) F4H-!9! !) )! )!) F$F LF 0FF$2B3!C3!3!&!S!!!| FA!R!Q!!!'!F8QdF! 8'&FXG&߀FP9 F (F8&F8F8F8AFFh0#S|߀' B ! B ! B! B݀ !݀ F$#!'!S|' F 0)FF @# FP9 FF9 8lF 8Q F8AFF$FF 'AF ##'߀ F"XR߀G'߀FP9R FF9 RFR$F @# ' FXG߀F8HCQ!9BQ! BQ߀!Q߀ FXRG߀F #R Q FZHCR!9BR! BR!Q BQ! BQ݀!Q݀ F$F RF .F#C3!B3!$ F$#B3!C3!3!!S!!!| FF$F 8&FF!253!S!! 3! FF!!!!R!!F8 ߀ FH!9ߠF8RF # F8RF$F XRGSFFH!9ݠF8F h# F 8#߀!! 3 F $F& ## ##!! 3 F,H!95! #߀ F!XG݀F $# F8H!9! 5! !  F 8F8H!9! 5! !  FDH!9! ߀!  5߀! F$F F$F FF.(4#!S!!2#! 3!53!+3!A3!P!@3 F!!T!*!+!,!!F3!b!!!F! T#P FD#߀ F$F 8T F8* ߀ F8+ ߀ F0ոF8!F0ڸF482#!S!!#! 3!53!+3!A3!!!!@3 F # F! D# F$FXGS߀F0b!T FF0!* F0(b F ## #b  F 8,F 0FF$F  F # P F D# F$F8FF0Fb8F:#ݠ #G{݂\( FXGS߀F0b!T FF0!* F0(b F ##b # F #P FH!+9߀FF 8F6H!+9߀#PPP F$F$F 8F98!F0ոF482#!S!!#! 3!53!+3!A3!!!!@3 F # F!0b(,!T ,!* FF 0bF 0bFFFF$F FF D# FF,F>R!!S!2 3!@3!53!A3!!!! !-!.!/!0 F"!!!!!!! !!F0 5! FXGF(0  R!߀ 5! F  F6H R!݀9 R!߀ 5! F$F <F8F > FF\IF H R!9 R! F FH R!9߀F$F0øFXG݀F0߸FXG݀F0 R! @! FF FR0 R! FF jF #  F,0#߀߀S A F 8BF"0## A F$F p߀F0A F$F0N( FF 0 FF0 G{F0 G{F -FF  F0߀SF$F0< F* RA wbFF80#.!/ .!0 A #߀ FF0#߀ F$F(#!߀!S߀ F0)w!) FFH.!-9)F$FF 1 F-42!3!4!A! !!d!5!@!!!!!RF#!!!!-F @ ! ! ! !A !+ !5 F\H ! ! !@! !A !+! !5! F) !* !4 ! ! F<H) !* !4 ! !! F4 !݀FFF84F86F8-dFd0F4F 8Ru!N݀ F 1F 8Ru߸!N݀ F$F 1F 8Ru߸!N݀ F$F4 Multiple Regression FF d1Fs4 Ridge Regression F$F 1Fn4 Cochran Regression F$F 1Fi4 Huber Regression F$F 1Fn4 Weighted Regression FF$F\T#B ݀!! Select Independent VariablesF(##R!!!3!!3!3 FFF 4FZT#B ݀!! Select Dependent VariableFF&##!!!3!@!3!3 FFF$F F!P9 F 87NFN xN>FNF$FFF\T#B ݀!! Select 'Calculated' VariableF2##!!݀!3!@!3!3 FFFP߀9 FL 9 CalculatedF!" ~ #N݀ F 8N7F$F 87NFN 1N>FNF$F$F 1FFF\T߀#B !! Select 'Weighting' VariableF 2##!!݀!3!@!3!3 F8 FFFP߀9 F 1F"  #N݀ F 8N7F$F$F$FFFH!9ݜFH!9߀FH!9߀FH!9߀FH!9F8@F8AF FF 1F&LY! "Ridge RegressionFF$LY! "Ridge factor: FF$F0ʸF v1Fg.LY! "Cochran Orcutt RegressionF&LY! "Cochran factor: FF$F j1Fh&LY! "Huber RegressionFF(LY! "Maximum deviation: FH!9ߴFeH!9߀FeF 8AF& $A߀! F0! F$F 11FF 8AFD A߀#! !  F$FFF 41F 0! F8 F$F 1F0! F ߀F!8 F$F$F$F ŚAF> b##> 1 #>߀ F88F 1F8FF$F \߀F 87NFN VN>FNF$FFF8T!!Variable for Lower 95% boundF*##!!8!3!@!3!3 F82 FP89 F8FFL29 Low 95% F 02 #N݀ F 8N7F$F 87NFN VN>FNF$FFF F>8T!!Variable for Upper 95% boundF*##!!8!3!@!3!3 FFF$FP89 F8FF83 FL39 High 95% F H3 #N݀ F 8N7F$F84F$F$F ߀F #>8 F 87NFN N>FNF$FFF:T!!Variable for Cook's "D" PercentF*##!!8!3!@!3!3 F8- FL-9 Cook D % F884FFF - #N݀ F 8N7F$F$F$F0 1#1߀ ݀ F >! Do you want a constant? !! YES | NO !@F 8 @߀F$F \F8F F ŔFF š1 Fn482#!J!!#!3!53!+3!A3!! !@3 F 8F#084#!J!!#!3!53!+3!A3!!@3 F$F  F4 improper data FF 8ŎFi4 CON:FFFFFFFF ň4FFFFFT!!*Calculating 95 percent bounds on estimatesF'6T!! and or Cook's DFs \FXGJ݀F 8#!!3 FF t߀F  n߀F H!29ߠFH!39ߠF$F 8dFXRG݀F H+!R9!R F ĚRF!8/߀ F 80 FD#!!J#!+3!@3!53!A3!!!! !-!!/!0 F ^߀FH!29FH!39F$F$F F9FF \F9$F$F$F 8ŬF F$FFF ! ! !4 !5 !? FHB! F) !* !4 ! ! FF!!253 F R! F2F8PM" "Multiple Regression AnalysisFF8PM" "Dependent Variable  FF PMcFZPM"HVariable Mean Std Err Coefficient Std Err T BetaFXRG݀F PMc!R "FF,PMc! #######.###!75R! "FF,PMc! #######.###!75R! "FF.PMc! #######.#####!75R! "FF 5R! F5,PMc! ######.####!75R! "FF 8&FcPM" NA "F$F0F 4 Ț5R! 5R! Fi(0(5R! 5R! F $F 5R! F0F$F FPMc!###.###!7"FF 8$FcPM" NA "F$F0F X#R F0F$F #R F05߀! F ɴzI>F0F>$F*05R! 5R! F$F F PMc! ######.#####!7"F 8BFc PM" NA "FF$F PMcF RF 0McFF ʤQ߀F F#!!53 F$FFFF > F XGFXG݀F"*H+!9+߀!݀ F F F$FX߀GFXGFH+!9ߠF rF ^FXGFL9 FL9 FXGFH+!9ߠF F ˴F \FXG݀FL9 FL9 F FFL9 F4޾ CORRELATION TABLE FF\4P F8Rw! F 8dw! F 8FF 8dFF*"#!+3!3!3!3!d!R!! FL9 CONSTANT FXGFL9݀ FR HFFF8FF"8u߀! F4 CON:FFFF # !& FH#! !& F0F! 8߀F0LY! "Calculating Condition indexF8+#+3!#3! FFF 2F 0F 0FFXG݀Fn (+! F0(+! FF$F (+! F0(+! FF$F ϞF ,߫pǝFF0N N F$F$F$F # !& F#!!53 F 8F ΌFFF4 CON:FFFFFFFFF R! FFF8PM" "Multiple Regression AnalysisFF PMcF8 FP9F #A ! F&PM" Standard error FF PMcFP9Ft #A ! F 4 FF #A ! F4 R-SQUARED  F,4  Adjusted R-Squared FFPM" F PMcF4 F VALUE FF #A ! F 4 FPM" F PMcF44 Degrees of freedom: Numerator A Fs&4  Denominator A F PM" FP9FF #A ! F PMcFFPM"1Percent chance of a higher value; if no relation F PMcF #A ! F.PM"Durbin-Watson statistic FF6PM""Squared deviations due regression "FF A Fe&PMc! #########.###!7A F 88FcPMc! NAFF$F4PM"!Squared deviations due residuals "F ԮA Fe&PMc! #########.###!7A F 8FcPMc! 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 0McFP9 FmF Q߀FfFFF$FFF.!!!!!A!d!5!@!!!!!RF#F @ ! ! ! !A !+ !5 F\H ! ! !@! !A !+! !5! F4 !݀FFF0F4F 8Ru!N݀ FRTd!!7Stepwise Regression Select Trial Independent VariablesF(##R!!!3!!3!3 F FF <FHT!!-Stepwise Regression Select Dependent VariableF&##!!!3!@!3!3 FFFP9 F$F ڊF r #N߀ F 87NFN$F َN>FNF$FFFLT!!0Stepwise Regression Select 'Calculated' VariableFa2##!!݀!3!@!3!3 FaFFP߀9 FL 9 CalculatedF!" ڄ #N݀ F 8N7F$F$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: FF8@F 8AF F 8AFp NA߀#! ! ! !  FFF0! F0! F \F$F F8F AF( ! ! !) !* !4 ! !B !C FH ! ! !* !) !4 ! !B݀!݀ !C߀!݀ F 483#!J!!#!3!53!+3!A3!!!@3 FF ! ! !B !C F0ոF8!F FH! F482#!J!!#!3!53!+3!A3!!!!@3 F) !* !4 ! ! F  F 4 improper data FF 8Fi4 CON:FFFFFFFF$F$FFF ! ! !4 !5 !? FHB! FFF!,9!! !A!d!5!@!!!!!RF#F(D !E !@ ! ! ! !A !+ !5 FpH !D !E ! ! !@! !A !+! !5! F) !* !4 ! ! F<H) !* !4 ! !! 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Onze bibliotheek van public domain programma's omvat op dit moment (herfst 1991) al meer dan zeshonderd disks. Daarop vindt u programma's op elk gebied, van tekstverwerker en database tot de leukste spelletjes, de fraaiste tekenprogramma's en de handigste utilities. Ook bevat onze bibliotheek een speciale afdeling voor public domain disks met Macintosh software, die te gebruiken zijn onder de ALADIN emulator. Deze MAC-PD serie bevat tot nu toe ongeveer vijfendertig disks. ******************************************************************** U vindt in het twee maandelijks tijdschrift "ST" (Onafhankelijk tijd- schrift van en voor gebruikers van Atari ST computers) een overzicht en een bespreking van de inhoud van de nieuwe public-domain diskettes. Dit tijdschrift bevat tevens een bestelkaart zodat U vlot over de software kunt beschikken. De Stichting ST geeft ook een speciale PD catalogus disk uit. Deze public domain disk is geproduceerd en gedistribueerd door: ************** Stichting ST afd. Software Bakkersteeg 9A 2311 RH LEIDEN ************** Ondanks onze controle komt het af en toe voor dat een diskje niet goed is gecopieerd.Mocht U dit overkomen, aarzel dan niet en stuur de defecte disk aan ons terug. U krijgt dan direct een vervangende disk toegestuurd. ************************************************************************ Teneinde het voor ons mogelijk te maken om productiefouten op te sporen en vervolgens in de toekomst te vermijden, zijn alle disks, geproduceerd door de Stichting ST, voorzien van een groen productienummer. ************************************************************************