Software of the Month Club 1996 August/Software of the Month Club 1996 August.iso/pc/dos/edu/kwikstat/xxks1.lzh/KS4.DOC

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                                   TexaSoft's
                               USING KWIKSTAT 4.1
                     Reference Guide, Condensed Disk Version

     (C)Copyright 1995 Alan C. Elliott

     (C)Copyright 1991, 92, 93, 94, 95 Alan C. Elliott For additional
     information on this product, contact TexaSoft, P.O. Box 1169, Cedar
     Hill, Texas 75106-1169 [phone], Fax: [phone],
     Compuserve:70721,3145, Internet: [e-mail]. Production
     team: Alan Elliott, Marcia Stoesz, Paul Witt, Nancy Witt, Carol
     Bigler, Doug Pollock, Melanie Walker. Program Testing Team: Leo Bolta,
     Shopsy's Foods, Canada Randy Hamlin, Senior Scientist, R&D Dept.,
     Hunt-Wesson, Inc. Dick Hawkins, Hunt-Wesson, Inc. Jack Holloway III,
     University of Phoenix Robert Jirsa, Southern CT State University Chip
     Kloos, Lab Manager, R&D Dept., Hunt-Wesson, Inc. Victor L. Landry,
     Ph.D., The Mercy Hospital of Pittsburgh, PA Gerard Leboucher,Labo
     Ethologie Et Psychoph, France Allen Lein, Professor Emeritus, UCSD
     Randolph Maheux, Tampa, FL Sukanya Misra, SMU Sanford Moos, Lab
     Manager, Enzo Labs Joseph Padgett, Raleigh, NC George Sadler, Ph.D.,
     USC Prof. Emeritus, Okla. City, OK Dr. Karl-August Schaeffer, Cologne,
     Germany Michael Stratil, Ph. D., Pembroke State University Wayne
     Woodward, Ph. D., SMU Carter Yeager, Boston University

     All rights reserved. No part of this book may be reproduced without
     prior permission. For information, address TexaSoft, P.O. Box 1169,
     Cedar Hill, Texas 75106-1169.

     No patent liability is assumed with respect to the use of the
     information contained herein. While every precaution has been taken in
     the preparation of this publication, the publisher assumes no
     responsibility for errors or omissions. Neither is any liability
     assumed for damages resulting from the use of the information herein.

     The KWIKSTAT software and manual ("documentation") are copyrighted by
     TexaSoft and are protected by both United States copyright and
     International treaty provisions. Before you can use this program on an
     on-going basis, you must pay a license fee. An order form is on disk
     in the file named KSORDER.TXT

     Important Information in the file LATENEWS.DOC: On the KWIKSTAT disk
     is a file named LATENEWS.DOC, which contains information about the
     program that is not in this documentation.

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     KWIKSTAT 4.1 Statistical Data Analysis
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     ===========================
     AN OVERVIEW OF KWIKSTAT 4.1
     ===========================

     KWIKSTAT is a statistical data analysis program. It was designed by
     professional statistical consultants and researchers to allow you to
     quickly and easily use the most commonly needed statistical data
     analysis procedures and graphs.

     KWIKSTAT REQUIREMENTS

     KWIKSTAT is a DOS program and may be run as either a stand alone
     application, or as a DOS window executed from within the "Windows"
     operating environment. It requires PC-DOS or MS-DOS version 3.0 or
     higher. If you are running Windows, version 3.1 or higher is required.
     Your computer should contain at least 512K or more of free RAM.
     KWIKSTAT graphics require an EGA or VGA compatible monitor. Many
     printers are supported. A mouse is optional.

     INSTALLATION

     In most cases, for a quick installation to a hard disk, you enter the
     command:

     INSTALL

     Follow the instructions on the screen. This procedure will install the
     program to a disk, and will automatically run the KWIKSTAT setup
     program. After installing KWIKSTAT, you can begin the program from the
     DOS prompt by entering the command KS.

     See the document on disk named KSWINDOWS.DOC for information on
     installing KWIKSTAT as a Windows icon.

     USING THE KWIKSTAT MENUS

     KWIKSTAT menus are similar to a windows menu system. The main menu bar
     contains five options: File, Edit, Analyze, Helps and About. Using the
     right and left arrow keys on the cursor pad, you can move the menu
     selection to one of the other menu bar options. Pressing the right
     arrow key once moves the menu bar option from File to Edit. The File
     pull-down menu vanishes and the Edit pull-down menu appears. Pressing
     the left arrow key moves the selection back to the File menu. Or,
     point to a menu option with the mouse and click.

     To select options from an extended menu (pulled-down), use the up and
     down arrow keys  to highlight the option you desire, then press the
     Enter key. Or, press the first letter of the option  name. If you are
     using a mouse, point to the selection with the mouse pointer and
     click. Here is brief description of each menu:
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     USING THE FILE MENU

     Before you can create a graph or calculate statistics, you must
     create a database and enter data. The options are:

     NEW DATABASE  - You must create a new database and enter data before
     doing any analysis or creating a  graph. The program creates and reads
     dBase (.DBF) type file format  databases.

     OPEN A DATABASE - Open an existing database. A  database must be
     opened so the program will know where the data is  located.

     SUBSET DATABASE - Creates a new database that is a subset of the
     current database.

     COPY/BACKUP - Creates a copy of the database.It is useful to create a
     duplicate copy in case the original copy is damaged.

     LIST (DISPLAY) THE CONTENTS OF THE DATABASE - Displays the information
     in the database to the screen.

     MODIFY OR DISPLAY DATABASE STRUCTURE - Allows you to view or  change
     characteristics about the database, including field widths and types.

     KILL - Deletes a database file from your disk.

     FILE UTILITIES - Imports information, creates reports, or outputs
     data.

     EXIT - Ends the program.

     USING THE EDIT MENU

     The EDIT menu contains options that allow you to enter new data
     into a database, edit data currently in a database, and other
     editing options:

     EDIT RECORDS - Change data already in the database.

     APPEND RECORDS - Add new records to the database.

     MISSING VALUE CODES - Define missing value codes for your database.
     Refer to the section titled "Setting Missing Value Codes".

     PACK DATABASE - Permanently erase all records marked for delete.

     ZAP - Get rid of all records in a database.


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     USING THE ANALYZE MENU

     The KWIKSTAT ANALYZE menu allows you to choose which analysis module
     to run. The menu items on the ANALYZE menu are:

     Descriptive Statistics
     Graphs - Descriptive & Comparative
     XYZ Visualization/Spin Plot
     t-tests and Analysis of Variance (ANOVA)
     Nonparametric Comparisons
     Regression & Correlation
     Crosstabulations, Frequencies, Chi Square
     Life Tables and Survival Analysis
     Data Generation, Concepts and Simulations
     2-Way Advanced ANOVA Designs (Professional edition)
     Multiple Comparisons (Professional edition)
     Advanced Regression (Professional edition)
     Time Series Analysis (Professional edition)
     Quality control graphs and charts (Professional edition)
     Pareto Charts (Professional edition)

     USING THE HELP MENU

     The KWIKSTAT Help system contains items to help you operate the
     program. These include:

     PROGRAM HELP - Contains general program help information
     TUTOR - Learn how to use the program
     DECIDE WHAT ANALYSIS TO USE
     CHANGE SETUP OPTIONS - Color, Printer, etc.
     AUTOHELP/Hints (On or Off)
     GO TO DOS, Return with Exit (Shell)

     TUTORIAL:TRY THIS EXAMPLE

     This short tutorial will give you a feeling for how to use KWIKSTAT.
     It will assume you are using KWIKSTAT on a hard disk. To begin
     KWIKSTAT, you must first be in the \KS4 directory on your hard disk.
     Use the CD (Change Directory) command from the DOS prompt to change to
     the \KS4 directory by using the command:

     CD\KS4   (or the directory where you installed KWIKSTAT.)

     Once in the \KS4 directory, begin KWIKSTAT with the KS command:

     KS

     The FILE pull-down menu will appear. (If the ANALYZE pull-down menu
     appears, press the left arrow key twice to open the FILE menu.) This
     example will use data already stored in a dBase ".DBF" file named
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     EXAMPLE. Follow these steps:

     Step 1 Select a data file: Open the database named EXAMPLE by
     selecting the Open a database option from the FILE menu, then choose
     EXAMPLE from the list of files. (If the EXAMPLE database does not
     appear on the list of databases, you may not have installed the
     program correctly.) Once the database is opened, a notice at the
     bottom of the screen tells you that the database named EXAMPLE is
     open, and it contains 50 records.

     Step 2 View the contents of the database: Choose the List (display)
     option from the menu.

     Step 3 Choose the ANALYZE pull-down menu: From the ANALYZE pull-down
     menu, choose the Graphs option. KWIKSTAT now switches to the Graphs
     module (which may take a few seconds). Soon, you will see the Graphs
     module menu.

     Step 4 Select a plot type: From the Graphs menu, choose the TIME
     SERIES PLOT option. The program now displays a screen with the fields
     available for use by  the graph. The field names appear in a pick box
     to the left of the screen, and an empty box appears to the right of
     the screen.

     Step 5 Select fields to plot: From the left screen (list of fields),
     choose which fields to plot in the time series plot. Choose the fields
     TIME1 and TIME2.

     When you choose a field, it will appear in the "Fields to Graph" box.
     After you choose the two fields, choose "Finished Choosing Fields."
     After a few seconds, a time series plot will appear containing two
     lines.

     The menu above the graph may be used to select user definable features
     of the graphic display. The options include:

     EXIT - exit the graph and return to the module menu.

     OPTIONS - choose options for the graph including title, axis names,
     footnote, and other options.

     PRINT - print the graph to your printer.

     CAP/PCX - capture the graph as a PCX file.

     GET COLORS - choose colors to be used to display the graph.

     +/- Smartpoint(tm) pointer used to select a datapoint on the screen.
     Information about the selected point will be displayed. (see step 7.)

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     Step 6 Control the plot menu: On all graphic screens in KWIKSTAT, a
     similar menu will appear at the top of the screen. If you want the
     menu to temporarily vanish, press the spacebar. Press the spacebar
     again for the menu to reappear. The  menu is active even if it is not
     shown.

     Step 7 Using SmartPoint(tm): If you are using a mouse, place the mouse
     pointer on a datapoint  on the screen and click. Or, if you are not
     using a mouse, press the + (plus) key, then use the cursor keys to
     position the + over a datapoint on the screen, and press Enter.
     Information about the  datapoint you selected will be displayed on the
     screen. This feature is particularly helpful in identifying points
     that are interesting or "outliers." Press Enter to return to the plot.

     Step 8 Select color options: Press G or click on the "get color"
     option. The color menu will appear. From this menu you can select
     color options.  Most plots contain the following "get colors" menu:

     Menu - returns to the main graph menu
     graph - changes graph colors
     screen - changes background screen colors
     labels - changes label colors
     default - returns plot to original default colors
     b&w - displays plot in black and white
     help - displays help system

     Some "get color" menus also contain the option:

     tile - paints the plot using tiles rather than solid colors

     Step 9 End this example: Choose Menu to return to the Graph menu.
     Choose Exit to return to the main graph menu. Choose Exit again to
     return to the module menu.

     TIP: When you choose to print or capture the screen, the menu will
     vanish, so the menu will not appear on the printout or PCX graphic.

     NOTE: You can also go through an on-screen tutorial on how to create a
     chart by choosing the TUTORIAL option on the HELPS pull-down menu.

     EXAMPLE 2: DESCRIPTIVE STATISTICS

     This example uses the data stored in the database named EXAMPLE.

     Step 1 Open the database: To open the EXAMPLE database, select the
     Open a Database option, then choose the EXAMPLE database.

     Step 2 Select an analysis module: Open the ANALYZE pull-down menu and
     choose the Descriptive Statistics option from that menu.
     KWIKSTAT switches to the Descriptive Statistics module.
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     Step 3 Choose analysis type: From the Descriptive Statistics menu,
     choose "Detailed statistics (single interval variable)." The program
     now displays the variables available for analysis from the database.

     Step 4 Select a field: Select the AGE variable. KWIKSTAT will perform
     calculations on the data in field AGE, and will produce a screen of
     descriptive statistics. At the bottom of this
     screen are several options.

     The Descriptive Statistics report screen menu options are:

     Exit - return to the main module menu

     graph - displays a graphic representation of the data

     view/print - allows you to print the information using the KWIKSTAT
     text viewer.

     ci - allows you to choose the confidence interval level.

     percent - allows you to choose what percentiles will be displayed.

     new var - returns you to the variable selection menu.

     Step 5 Display the graph: Choose the Graph option. This screen allows
     you to examine the distribution of numbers in the variable being
     analyzed (AGE in this case.) Several options on this menu that were
     not described in the previous example are:

     exit - returns to the descriptive statistics summary screen.

     mean CI off/on - displays a normal curve on the histogram, and shows
     where the mean and confidence interval is located on the box plot.

     print - prints the screen to the printer.

     + (plus) and -(minus) - redraws the histogram using more or fewer
     classes. dist. off/on -- allows you to display a cumulative
     distribution for the data.

     cap/PCX - captures the graph in a file using the PCX graph format.

     b&w or color - displays the graph using black and white or color.

     Step 6 End this tutorial: Choose Exit to return to the previous
     screen. Choose Exit again to return to the module menu. End KWIKSTAT
     by choosing the Quit option. This ends the tutorial.


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     ===========================
     USING THE KWIKSTAT DATABASE
     ===========================
     The FILE and EDIT pull-down menus are used to manage your data.

     Here is a roadmap to help you find the area of this chapter that
     will be most helpful to you according to your database needs:

     YOUR DATA IS ALREADY IN A DBASE DATABASE: If your data is already in a
     database, you may not have to use any of the procedures in this
     chapter. Simply copy your database into your KWIKSTAT data
     subdirectory, and it will be accessible immediately. If you have
     missing values, you should review the section titled "Missing Value
     Codes." If you have memo fields in your database, review the section
     called "Using dBASE files."

     YOU NEED TO ENTER YOUR DATA: If your data is not already in a file,
     you will need to create a database and enter your data. In this case,
     read the next few sections beginning with "An Overview of Database
     Creation and Design" and perform the two examples to learn how to
     create a KWIKSTAT database. Your data is in a non-dBASE file: If your
     data is already on the computer, but not in a dBASE (.DBF) file, you
     can usually import the data into KWIKSTAT. See the section titled
     "Using data from other programs" later in this chapter.

     DATABASE CREATION AND DESIGN

     The process for entering data and performing an analysis can be
     summarized in three steps:

     Step 1: Create a database.
     Step 2: Enter data into the database.
     Step 3: Choose an analysis option.

     OPTIONS FOR CREATING A NEW DATABASE

     Before you can enter data into a database, you must create a new
     database. The New Database option on the FILE Menu is used to
     create a new database. The structure, or layout, of a database must
     be described before you enter your data. KWIKSTAT allows you to
     create a new database in two ways:

     1. Choose from a predefined structure or
     2. Create a customized database structure.

     The following sections describe these two options.




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     CREATING A DATABASE FROM A PRE-DEFINED STRUCTURE

     A pre-defined structure is a "blank" database designed for a
     particular analysis type. Using a pre-defined database allows you to
     create a database for your analysis without having to worry about what
     fields are necessary, what type they should be, their width, and so
     on.

     The list below contains examples of some of the pre-defined database
     descriptions available when you choose to create a New Database.
     Choose the option that will create a database structure for the kind
     of analysis you will perform. (You may have to scroll to see some of
     the options.)

     CREATE A CUSTOMIZED DATABASE
     SINGLE VARIABLE, DETAILED STAT, HISTOGRAM, STEM & LEAF
     GROUPED HISTOGRAM, STATISTICS OR STEM & LEAF
     SIMPLE BAR CHART: LABEL AND VALUE
     PIE CHART: LABEL AND VALUE
     ETC...

     CREATING A CUSTOMIZED DATABASE

     If none of the pre-defined database structures meet your needs, you
     need to create a customized database. The following sections describe
     how you create a customized database structure to match your analysis
     needs.

     SPECIFYING FIELD TYPES REQUIRED BY AN ANALYSIS

     When you create a new database, you must specify certain
     information about each data field, including the field name, type,
     width and number of decimals (if any):

     1. The FIELDNAME: A fieldname must be 1 to 10 characters in length and
     MUST begin with a character (a to z) and can contain letters, numbers
     and the underscore character "_". Upper and lower case DO NOT matter,
     since the name is always translated into all upper case.

     2. The TYPE:Type may be . . .

     CHARACTER - May contain any characters.

     NUMERIC - Must contain numbers only. Example legal numbers are:1.00,
     -4.32, 6, 10000. Example illegal numbers are: 450-23-1232, $23.95,
     40%. (For data like these, use the character type.)

     DATE or LOGICAL fields can be created in KWIKSTAT, but KWIKSTAT
     analyses will only use numeric and character fields. Thus, date and
     logical fields are treated the same as CHARACTER fields, except for
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     subsettings and in transformations (Replace).

     3. The WIDTH of the field: Choose a width so that the maximum number
     of characters needed will fit into the field. For DATE or LOGICAL
     types, field widths are automatically set at 8 or 1 respectively.

     4. DECIMALS:Decimals are only valid for numeric fields. This specifies
     to KWIKSTAT how many decimals to retain in the field. For example, if
     you wish to store numbers that are dollar prices, your data may look
     like "9999.99". This field would have a width of 7, with 2 decimals.

     KWIKSTAT DATABASE LIMITATIONS

     Maximum of 250 fields.
     Maximum width of a field name is 10 characters.
     Maximum width of a cell is 60 characters (15 for numbers).
     Dates are always 8 characters and logical fields are 1 character wide.
     Memo fields are not supported.

     DATABASE EXAMPLES

     This section provides you with two examples of creating a KWIKSTAT
     database. Go over these examples before creating your own database and
     performing your own analysis. Following these examples will answer a
     number of questions you may have about how to use KWIKSTAT.

     EXAMPLE 1, USING A PRE-DEFINED STRUCTURE

     This example shows how you would perform an independent group t-test
     in KWIKSTAT using one of the pre-defined database structures. In this
     example, 13 plants were randomly allocated to two groups. Group one
     received the present fertilizer and group 2 received a newer
     fertilizer. After a period of time, you observed the heights of the
     plants. The results are:

     Data for independent group t-test (fertilizer study)

     Present  Newer Fertilizer
     46.2 cm   51.3 cm
     55.6      52.4
     53.3      54.6
     44.8      52.2
     55.4      64.3
     56.0      55.0
     48.9

     In order to enter this into a database, you must assign group numbers
     (or letters) to each group. For example, we will call the "Present
     Fertilizer" group 1 and the "Newer Fertilizer" group 2.

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     The database will include thirteen records (one for each plant) and
     two fields (one for the response and one for the group indicator).
     When entered into the database, the data will look like this:

     Group  Height
     1      46.2
     1      55.6
     1      53.3
     1      44.8
     1      55.4
     1      56.0
     1      48.9
     2      51.3
     2      52.4
     2      54.6
     2      52.2
     2      64.3
     2      55.0

     Step 1 Create the Database: From the FILE Menu on the main KWIKSTAT
     menu screen select New database.

     Step 2 Name the Database: You will be prompted to enter the name of
     the database you are creating. Type a name (e.g., TTEST (maximum of 8
     characters)) and press Enter.

     Step 3 Select a Structure type. A screen with the instruction "Choose
     the database type to create from the menu below" will appear. Since
     you are performing an independent group t-test, you can select the
     option titled INDEPENDENT GROUP T-TEST OR ANOVA from this list. This
     process automatically builds a database structure suitable for
     entering data for this kind of analysis. In this case, the database
     will contain a grouping field GROUP (where you will enter a 1 or 2,
     the fertilizer type) and an observation field OBS (where you will
     enter the height.)

     Step 4 Enter the Data: A data entry screen will appear where you will
     enter the data. In the spreadsheet type of entry, the field names are
     listed at the top of the screen, and the record numbers at the left
     side. The data you will enter in the first record is 1 (press Enter)
     and 46.2 (press Enter). When you type the 46.2 and press Enter, your
     cursor will automatically move to record number 2, where you will
     enter 1 and 55.6, and so on.

     Enter the data for the thirteen records. For each record of a "Present
     Fertilizer" observation, enter "1" for the GROUP variable. For the
     "Newer Fertilizer" observations enter a "2" for the GROUP variable.
     The eighth record is 2 and 51.3. Once all 13 records have been
     entered, the program will be waiting for a 14th record to be entered.

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     Since there is no 14th record, press the F7 function key (Exit) to end
     the data entry process. KWIKSTAT will return to the Data main menu.

     Step 5 Performing the Analysis: From the main KWIKSTAT menu, select
     ANALYZE. From the ANALYZE pull-down menu, select t-tests and Analysis
     of Variance (ANOVA). The menu will appear.

     Select Compare independent groups (t-test, ANOVA). A field selection
     dialog box titled "Choose a grouping variable" will appear with the
     following options:

     Exit Choices
     GROUP   (N)
     OBS   (N)

     Select GROUP as the grouping field. Another dialog box will appear
     titled "Choose a data (numeric only) variable" with the same options.
     Select OBS, as the data variable (OBS contains the height data). Note:
     If you want to cancel the analysis, you would choose the Exit Choices
     option.

     KWIKSTAT will now perform the calculations and display another dialog
     box on the screen with the following options:

     A) View or print the calculated results
     B) Graphical Comparison
     Q) Quit, return to main menu

     Choose the "A)View..." option. The results of the analysis will appear
     on the screen in the KWIKSTAT viewer. Select Exit (F7) to exit the
     viewer and return to option menu. Choose "Q)Quit..." to return to the
     module menu. Select "X)Exit..." to return to the main KWIKSTAT menu.

     EXAMPLE 2, CREATING A CUSTOMIZED DATABASE STRUCTURE

     This example shows you how to enter data and perform some simple
     statistics and graphs. It will show you both the spreadsheet and
     database entry screens. The data that will be used is listed below.
     The GRADE variable is the grade received in the class, AGE is age, SEX
     is sex, WT is weight and SCORE is the score on a pre-test (maximum of
     25 points). In database language, these variables are called fields.

     Step 1 Choose the New database option: From the FILE menu, choose the
     New Database option. You will be prompted to enter the name of the
     database. Enter the name MYDATA (a DOS compatible filename).

     Step 2 Choose Customize option: Once you have entered a filename for
     the database, a list of database structures will be displayed similar
     to the list on page 2-4. For this example, choose the CREATE A
     CUSTOMIZED DATABASE option.
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        GRADE    AGE   SEX   WT    SCORE
     1  A        18     M   165    22.3
     2  B        19     M   145    22.8
     3  B        17     F   122    22.8
     4  C        18     M   196    18.5
     5  B        17     M   188    19.5
     6  B        18     F   140    23.5
     7  C        19     F   121    22.6
     8  B        20     F   112    21.0
     9  C        19     F   122    20.9
     10 A        18     M   176    22.5
     11 B        18     M   165    23.3
     12 A        19     M   135    21.8
     13 A        18     F   121    24.8
     14 C        19     M   186    16.5
     15 B        17     M   148    18.5

     Step 3: Define the Database Structure: For each field (each item of
     data) in the database, you must specify the following information:

     A name of the field - something to identify it

     The type of data - is it numeric or character?

     The width of the field - enough to hold the biggest entry

     Decimal places - if needed

     For the data in this example, you will use the following information:

     Field name  Type  Width  Dec
     GRADE       C     2
     AGE         N     3
     SEX         C     2
     WT          N     4
     SCORE       N     5       1

     The GRADE and SEX variables are of type "C" (Character) and the rest
     of the variables are numbers "N". Only the SCORE variable requires a
     decimal value. Enter the information about the database structure into
     the database definition screen.

     Step 4 Enter the data: A data entry screen will appear listing the
     names of all of the fields and an area to enter the data. KWIKSTAT
     includes two types of data entry screens, database type and
     spreadsheet type. In the Setup routine, you chose one of these two
     entry options. The following discussion shows you how to enter data in
     the spreadsheet screen.

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     TIP: You can toggle between spreadsheet entry mode and database entry
     mode by pressing the F8 (Switch) key.

     Step 4A Using a spreadsheet entry screen: The spreadsheet screen, as
     shown in figure 2.7 looks similar to a spreadsheet. If you prefer to
     use the database entry mode, skip to the section titled "Using a
     database entry screen."

     The names of the database fields (Grade, Age, etc.) are listed at the
     top of the screen (columns) and the record numbers are listed down the
     left side of the screen (rows). Initially, since you do not have any
     records entered into the database, the only row displayed is the -ADD-
     row, which indicates that you are adding a new record.

     To enter data into the database, begin typing the entry for the first
     field (GRADE). Type an A (upper case), then press Enter. Your cursor
     moves to the next field (AGE). Type 18 and press Enter. Type upper
     case M and press Enter. Continue until you have entered 22.3 in the
     SCORE field. When you press Enter after entering 22.3, a new row
     appears to allow you to enter the second record of information, and
     your cursor moves to the first field of this record. Continue entering
     information in the spreadsheet until all records are entered. If you
     make a mistake on a record, you can use the right or left arrow keys
     to move your cursor and correct the mistake. If you discover that you
     have made an error in a previous record skip to step 5 now. When you
     have finished entering the information in the database, end the entry
     procedure, press  F7 (Exit.).

     Step 5 Correcting errors in the database: Before exiting the data
     entry screen, you can correct errors in data entry mode by using the
     F2 key to toggle into Edit mode. The edit screen is similar to the
     screen used to enter data. Use the cursor keys to move to the field to
     edit, and change the value. Exit the edit screen/data editor by
     selecting the F7 (Exit) command. You will return to the KWIKSTAT main
     menu.

     Step 6 Perform a Descriptive Statistics analysis: Once you have
     entered your data into the database, you are ready to perform one or
     more analyses. From the main KWIKSTAT menu, choose the ANALYZE
     pull-down menu. Choose the Descriptive Statistics option on the
     ANALYZE menu. After a few seconds, the Descriptive Statistics menu
     will appear. This menu lists the options you can choose from the
     Descriptive Statistics module.

     Step 7 Select Detailed Statistics: To calculate detailed statistics
     for a variable in your database, select the option called "Detailed
     Statistics (single interval variable)". A screen will appear prompting
     you to specify what field to use in the calculations. Select AGE. The
     detailed statistics screen for the selected variables will appear on
     the screen. Once you have examined these results, select Exit to exit
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     the screen. This output is discussed later in "Using Descriptive
     Statistics."

     USING THE KWIKSTAT FILE MENU

     The FILE Menu is the first menu you normally use when you begin
     KWIKSTAT. From this menu, you open a database or create a new
     database. Either way, you usually must have data in a database before
     you can perform an analysis. This section describes the options on the
     FILE Menu.

     NEW DATABASE

     When you choose New Database from the FILE Menu, you will be prompted
     to enter the name of the database. Enter a file name such as MYDATA.
     (Eight characters maximum.) Once you have entered a filename for the
     database, you can choose from a list of pre-defined database
     structures, or create your own. See Examples 1 and 2 later in this
     chapter for a tutorial on using a pre-defined structure or creating a
     customized database structure.

     OPEN A DATABASE

     The Open a database to use option on the FILE Menu allows you to
     access information in a dBASE file that you created in KWIKSTAT, in
     dBASE, or in any other program that creates .DBF files.

     If the database you want to use is not in the current (default)
     directory, you can temporarily change the default directory by
     selecting "Choose New Path (F2)". You will be asked to enter a path
     name (such as \DB3). Then, the .DBF files in that directory will be
     displayed in a list, and you can choose the database to use from that
     list. Another way to open a database that is not in the default
     directory is to enter it by name. To do this select "Enter Choice by
     Name (F3)". You will be prompted to enter the name of the database to
     use. For example, if the database you want to use is MYDATA.DBF and it
     is in the \DB3 directory, you would enter \DB3\MYDATA. Do not include
     the .DBF extension in the name.

     Once a database is open, you will see its name at the bottom left of
     the screen, along with the number of records in the database. Once a
     database is open, you can edit, pack, modify, set missing values,
     subset and list the database using the other options on the FILE Menu.

     SUBSET A DATABASE

     The Subset database option on the FILE Menu allows you to create a new
     database from an old one. The new database can be a subset of the old
     one, using a conditional criteria for outputting information from the
     old database to the new one.
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     For example, suppose you have a database with a field GROUP with
     values 1, 2, 3, 4 and 5. You want to create a database that does NOT
     include Group 5. After choosing Subset database from the FILE Menu,
     you are asked for the name of the new database. For example, your new
     database might be named NO5.DBF. You are asked for the field name to
     be used in the selection criteria. In this case, you would choose the
     field named GROUP. Next you must enter the selection relationship. It
     will be described as a numerical expression. The conditional operators
     you may use are:

     = (equal)
     > (greater than)
     < (less than)
     >= (greater than or equal to)
     <= (less than or equal to)
     <> (not equal to)

     For example, you would enter the condition

     GROUP <5

     You can also use the logical operators .NOT., .AND., and .OR.. It is
     important that a dot (.) appear before and after each logical
     operator. For example, a conditional expression to include only groups
     1 and 5 would be

     GROUP = 5 .OR. GROUP = 1

     Other examples of conditional expressions are

     GROUP > STATUS
     GROUP < WEIGHT*HEIGHT
     TIME1 = TIME2*1.96
     SEX <> 'F'
     TIME1 <=20 .AND. SEX = 'M'

     When you choose the Subset option from the FILE Menu, a Subset dialog
     box appears on the screen. There are two items you must enter in the
     Subset dialog box. First is a name for the new database. This must not
     be the same name as the current database. Then, you must enter the
     subset criteria. Examples of subsetting criteria are:

     Once you have entered the filename and condition, press the F7 key to
     begin the subset procedure. A database with the name you specified
     will be created, containing the records selected by your condition
     statement. Note: When creating conditional expressions for subsetting,
     use the functions  described in the table "Database Calculator
     Functions" later.

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     COPY/BACKUP DATABASE FILE

     The Copy/Backup Database File option on the FILE menu allows you to
     quickly create a backup copy of your database information. This is
     recommended, particularly for large database because sometimes
     databases become corrupt or are made unusable for some other reason.

     LIST RECORDS

     The List (display) the contents of a database option on the FILE Menu
     allows you to look at the information in your database.

     MODIFY OR DISPLAY STRUCTURE

     The Modify or Display database structure option on the FILE Menu
     allows you to display the structure of your database, and allows you
     to change characteristics about the database structure. When you
     choose to display the structure, a list of all field names, their
     types, widths and decimals (if any) are listed. When you choose to
     modify a database, you are given a chance to modify the
     characteristics of each field. Your options are:

       Delete the Field
       Change Name of Field
       Change Type of Field
       Change Width of Field
       Change Number of Decimal Places

     If you change the type of field, say from character to numeric, the
     program will attempt to convert the contents of the field to its new
     type. When you modify a database, you will be asked to enter the name
     of a new database. This means that the modified database will be in a
     new file, and your old original database will remain intact. If you no
     longer want the old database, you must delete it by choosing the Kill
     database file option from the FILE Menu.

     KILL (DELETE) A DATABASE

     The Kill - Delete database file option allows you to delete a database
     and its related missing values files (if any.)

     FILE UTILITIES - EXPORT, IMPORT, REPORT

     This menu provides several data utilities. When you choose this
     option, the KWIKSTAT utilities menu appears. It allows you to choose
     from these options:

     Export data to an SDF file -- This option allows you to write out the
     data in a database to an ASCII file. This option is useful when you
     are wanting to transfer data from your KWIKSTAT database to another
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     program that does not read .DBF files. See "Exporting Data" later in
     this chapter.

     Import data from a Comma Delimited file or from a 1-2-3 file -- See
     the section below titled "Entering or Importing Data" for information
     on how to import data into a KWIKSTAT database.

     Report - Allows you to produce a report using the data in your
     database. See the section titled "Printing a Report" later in this
     chapter

     Sort - (Professional Edition Only) Allows you to sort your database in
     ascending or descending order using any field in the database.

     EXIT KWIKSTAT

     Use this option to end the KWIKSTAT program.

     USING THE KWIKSTAT EDIT MENU

     The EDIT menu allows you to modify and manage data in a KWIKSTAT
     database. Often, after you have created a database, you need to add
     new data or modify the current data. You can also add new fields,
     calculate new variables and delete fields or records. This section
     describes the options you can access from the EDIT menu.

     EDIT RECORDS, ADD, DELETE OR REPLACE FIELDS

     When you choose the Edit records option, the KWIKSTAT data editor will
     appear. The data editor is described in detail in the section titled
     "Using the KWIKSTAT Data Entry Screens" later in this chapter.

     APPEND RECORDS, FROM KEYBOARD OR FILE...

     The Append records option allows you to add new records to an existing
     database. You have three data entry options:

     Enter data from keyboard - Allows you to enter data by typing it on
     the keyboard.

     Enter data from a text file - Allows you to import data from an ASCII
     file. See the Section titled "Entering and Importing Data" later in
     this chapter.

     Append data from a dBASE file - Allows you to append data from another
     in this chapter.




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     MISSING VALUES CODES

     Sometimes in the collection of data there are values that are lost or
     cannot be gathered. These are called "missing values". When such
     values occur, it is important for the program to know that the values
     are missing so that statistical calculations may take this into
     account. Missing values are usually designated as an impossible value.
     For example, the missing values designated for the variable AGE may be
     -9, since it is impossible for the variable AGE to have the value -9.
     When the program is asked to calculate the mean of age, for example,
     it will ignore those records where AGE is -9 in that calculation if -9
     has been specified as the missing value code. In most KWIKSTAT
     procedures, there is a casewise deletion of the record from
     calculation whenever a missing value is encountered.

     Once you designate a missing value code for a variable, it is up to
     you to make sure that this code gets placed into your database in the
     proper records and fields.  For example, if you have designated -9 as
     the missing value code for AGE, you must make sure that in your
     database a -9 appears in the field AGE if that data is missing or
     unknown.

     The Indicate missing value codes option on the FILE Menu is used to
     set up these values. When this option is selected, the program will
     display an entry screen that is similar to a data entry screen. You
     may enter one missing value for each field name. The missing value
     must obey the definition of the field in terms of length and type.

     Once missing values are entered, they are stored on disk in a file
     named filename. MV, where "filename" is the name of the designated
     database. If a new variable is created using the transformation
     procedure, its missing value is appended to the missing value file.

     You may change or correct the missing values for a database at any
     time by calling up this option. If missing values are already
     designated for the database, they will be displayed on the entry
     screen, and you may edit them or accept them as they are.

     Note: If missing values are NOT used, and there is a blank numeric
     variable in a calculation, it may be treated like the value 0 (zero),
     so it is important to use missing values if your data contains such
     entries. Otherwise, the statistical calculations may be in error!!

     PACK DATABASE

     The records marked for delete are not actually erased from the file at
     this point. However, they will be ignored in most analyses, and will
     continue to be displayed when you edit the database. See "Edit Mode
     Options" later.

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     If you want to permanently get rid of the records you have marked for
     delete, choose the Pack procedure from the FILE Menu. This procedure
     erases all "deleted" records from the database.

     ZAP - GET RID OF ALL RECORDS

     The Zap option in the EDIT menu allows you to quickly erase all
     records from a database. To use this option, open a database, then
     choose Zap.

     USING THE KWIKSTAT DATA ENTRY SCREENS

     If there is a need to change data already in a database, you may
     choose the Edit records option from the EDIT menu. Editing is similar
     to entering data. Use the up and down arrow keys to move from field to
     field within a record and type in any change you want to make in the
     field. The section below describes the menu bar options available to
     you in the data entry screen.

     USING APPEND & ENTRY SCREEN MENU BAR OPTIONS

     When you are appending information to the database, there are several
     function key options that you can choose. These options are listed at
     the bottom of the entry screen.

     APPEND MODE OPTIONS
     To choose an option, press the function key related to the option, or
     point to the option with the mouse and click. The options available
     are:

     F1 Help - Displays the KWIKSTAT Help menu.

     F2   Edit - Toggles between edit mode (correct current entries) and
     append mode (add new entries).

     F7 Exit- Exits entry mode and returns you to the main KWIKSTAT menu.

     F8 Switch - Switches between spreadsheet type entry and database entry
     mode.

     F10 Print - Print the current record to the printer or to a file.

     EDIT MODE OPTIONS

     When you are in edit mode, a slightly different menu bar appears
     containing the following items:

     F1 Help - Displays the KWIKSTAT Help menu.

     F2 Append - Toggles between edit mode and append mode.
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     F3 Delete - Marks one or more records for deletion. When you choose
     this option you will be able to choose from the following options:

     A) Mark this record for delete
     B) UNMark all records where fieldname = value
     C) Mark all records for delete where fieldname = value
     D) UNMark a range of records
     E) Mark a range of records
     Q) Quit this option

     You can mark as many records as you choose. Once you have marked the
     records for delete, you can pack the database using the Pack option in
     the Edit pull-down menu.

     ANALYSIS TIP: Marking records for delete is a quick and simple way to
     do an analysis on a portion of your database. Mark the records you
     want to eliminate from an analysis, then perform the analysis.
     KWIKSTAT will ignore the deleted records. Later, you can undelete the
     records.

     Note: A ^U (Ctrl-U) also deletes and single undeletes records. Place
     your cursor on the record to delete or undelete, and press ^U.

     F4- Erase/Insert - the current record permanently from the database.
     (Only in spreadsheet entry mode.) When you choose this option the
     following menu items will appear:

     A) Erase records beginning with record #
     B) Insert blank records before record #
     Q) Quit this option

     To erase one or more records, display the record in Edit mode.
     Highlight the record to erase, and press the function key F4. You can
     then choose to erase the single record or a range of records.

     F5 Goto - Go to a record number.

     F6 Undo - Returns last record changed to its previous values.

     F7 Exit - Exits entry mode and returns you to the main KWIKSTAT menu.

     F8 Switch - Switches between spreadsheet type entry and database entry
     mode.

     F9 Field - Insert or Delete a field in the database or Replace the
     contents of a field. See "Creating New Fields and Replacing the
     Contents of a Field" below.

     F10 Print - Prints the contents of the current record to a printer or
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     file.

     CREATING NEW FIELDS AND REPLACING THE CONTENTS OF A FIELD

     Using the F9 Field option in the Spreadsheet data entry screen, you
     can create new blank fields of any field type, and place information
     in those fields that is either a numeric or character expression. The
     option menu displayed when you choose F9 Field is:

     A) Insert a new field after the field: fieldname
     B) Delete the field named: fieldname
     C) Replace contents of field: fieldname
     D) Set missing values for fields
     Q) Quit this option

     The following sections "Creating a New Field" and "Replacing the
     Contents of a Field" describe these procedures.

     CREATING A NEW FIELD

     You may create a new field in a database within an edit screen by
     choosing the F9 (FIELD Insert) option. After creating a new field, you
     can then use the F9 (FIELD Replace) option to place a value in the new
     field.

     When you choose the Field/Insert option in the edit screen (F9), you
     will be prompted to enter information about the new field.

      Define a name for the new field
      Define the field type
      Define a width for the new field

     For numeric variables,
      Define the number of decimals, if any
      Define a missing value code. If none is selected, it is assumed to
      be 0 (zero).

     After entering a new name for the field, you will be prompted to enter
     the field type, width and decimals (if numeric). For example, if your
     new field is numeric with a width of 8, and 2 decimal places, you will
     enter

     N,8,2

     If the field is Character with a width of 3, you would enter

     C,3

     After you enter the type and width information, you will be asked if
     you want to enter missing value codes.
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     Note: All of the normal restrictions of defining a field remain.

     TIP: To create a new field containing a new value that is a numeric
     transformation of other fields, first insert the new field using the
     F9 Field/Insert option, then use the F9 Field /Replace option to place
     the value in the new field.

     REPLACING THE CONTENTS OF A FIELD (TRANSFORMATIONS)

     You can use the F9-Field Replace option in the Edit screen to replace
     the existing contents of a field, or place new information in a newly
     created blank field. KWIKSTAT provides a number of numeric and
     character functions to enable you to do this.

     For example, if you wanted to replace the contents of the field NEW
     with the values TIME1/AGE:

     Step 1 Highlight the field to replace: In the edit mode, highlight the
     field whose contents you want to replace. Press the F9 (Field) option,
     and choose "Replace the Contents of a Field" option from the Field
     menu. A dialog box will appear.

     Step 2 Specify which records to replace: The default is ALL, which
     means all records in the database. Or, enter a range such as 1-20,
     which would mean only perform the replacement in records numbered 1
     through 20. Then, press Enter.

     Step 3 Specify what to place in the field: For example, enter the
     formula TIME1/AGE in the Replace With entry field, where TIME1 and AGE
     are two other fields in the same database.

     Step 4 Specify a condition for replacing (if any): The default is
     NONE. For example, if you only want the replacement to be for records
     whose value of AGE is greater than 20, you would enter the expression
     AGE>20 in the condition entry field.

     Step 5 Begin the replacement: Press F7 when you have finished entering
     the Replace information, and the replace will begin. When it is
     finished, you will return to the edit screen.

     USING DATABASE AND MATHEMATICAL EXPRESSIONS

     The kinds of expressions you can use in Subset and Replace options are
     described below. KWIKSTAT supports two kinds of expressions.

     1. Database expressions (most normally used.)

     2. Mathematical expressions (signaled with an = preceding the
     expression.)
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     USING DATABASE EXPRESSIONS

     Database expressions allow the use of common character, numeric, date
     and logical fields in the expression. Use the mathematical expression
     only when you must use mathematical functions not in the normal
     database expression list. Here are the usage criteria:

     In a REPLACE WITH field: Use either a database expression or a math
     expression.

     In a CONDITION field: Use only a database expression.

     Most expressions can be handled with the database expressions. If you
     find that you cannot create an expression using the database
     functions, go to the section titled "Using Mathematical Expressions"
     later in this chapter. The following information on how to use
     expressions is  useful for both the database and mathematical
     expression types:

     Arithmetic operators:
     Add    +
     Subtract  -
     Divide  /
     Multiply  *
     Exponentiation   ^ (Mathematical expressions only)

     For Character fields, the database calculator supports the
     operation:
     Add    + (appends one string to another)

     Following are a few examples of correct expressions:

      AGE/HEIGHT
      LTRIM(FIRST)+' '+LAST
      (AGE*TIME1)+3.2

     Note: Literal strings included in expressions must be surrounded by
     single quotes. For example, 'Hello' is a literal string. Character
     field names are used without quotes. For example, NAME is a field
     name. A correct string expression using these two strings would be:

     'Hello '+NAME

     DATABASE CALCULATOR FUNCTIONS SUPPORTED

     The following functions may be used in expressions both in the
     "Replace With" and "Condition" fields. In this table the arguments
     have the following meanings

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     NUM - Numeric argument
     STG - String (Character) argument
     DATEFMT - Date argument, MM/DD/YY
     LOGICAL - T or F
     LEXP - Logical Expression
     AEXP - Any Expression
     | means OR, choose one or the other option.
     [ ] means optional argument

     Database Calculator Functions

     Name       Meaning              Example of use        Type
     -------    ------------------------------------------------
     ABS        Absolute value       ABS(NUM)              N
     ASC        Ascii value          ASC(STG)              N
     AT         AT Find              AT(STG1,STG2)         N
     CALENDAR   Number to Date       CALENDAR(NUM)         D
     CAPS       First Letter Cap     CAPS(STG)             C
     CHR        Number to String     CHR(NUM)              C
     DATE       System Date          DATE()                D
     DELETED    Is record Deleted    DELETED()             L
     IIF        Logical If           IIF(LEXP,AEXP1,AEXP2) CNL
     INT        Integer Round        INT(NUM)              N
     JULIAN     Date to Number       JULIAN(DATE)          N
     LEFT       Left string          LEFT(STG,NUM)         C
     LEN        String Length        LEN(STG)              N
     LOWER      Lower Case           LOWER(STG)            C
     LTRIM      Trim Left            LTRIM(STG)            C
     MAX        Max of 2 Nums        MAX(NUM1,NUM2)        N
     MIN        Mini of 2 Numbers    MIN(NUM1,NUM2)        N
     REPLICATE  Repeat String        REPLICATE(STG,NUM)    C
     RIGHT      Right String         RIGHT(STG,NUM)        C
     RTRIM      Trim Right           RTRIM(STG)            C
     SPACE      Space                SPACE(NUM)            C
     STR        Number to String     STR(NUM)              C
     STRING     Create String        STRING(NUM,NUM|STR)   C
     RIGHT      Right String         RIGHT(STG,NUM)        C
     STUFF      Stuff String         STUFF(STG,NUM,NUM,STG2)C
     SUBSTR     Extract String       SUBSTR(STG,NUM,[NUM]) C
     TIME       System Time          TIME()                C
     TRIM       Trim blanks          TRIM(STG)             C
     UPPER      Upper Case           UPPER(STG)            C
     VAL        String to Number     VAL(STG)              N

     The following functions are supported only in the "Replace With" entry
     field, and only for numeric field types. You MUST precede expressions
     using these functions with an = sign.

     An example of the RECODE function, which appears on the following
     table is:
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     =RECODE(SCORE,1,AGE,10,15)

     The five arguments in the RECODE function are:

     No.  Example  Meaning
     1    SCORE  Field to use in compare
     2    1  Value to assign if comparison is true
     3    AGE  Value to assign if comparison is false
     4    10  Low range of field to compare
     5    15  High range of field to compare

     Thus, this example means that the value of the RECODE is 1 if SCORE is
     between 10 and 15, else the value is the current value of the AGE
     field for that record.

     USING MATHEMATICAL EXPRESSIONS

     In the REPLACE WITH field, the default expression type is the database
     type. In order for an expression to be evaluated as a strictly math
     expression, you must place an equal sign "=" at the beginning of the
     expression.

     The major difference between the database and mathematical expression
     types are their capabilities. The database expression can handle most
     common calculations, including simple math, string evaluation, and
     date evaluation. The math expression can be used only for strictly
     numeric calculations using one or more of the functions listed in the
     table below, or that uses the exponentiation operator.

     For example, if you want to perform the calculation WEIGHT/HEIGHT, you
     can enter the expression as-is in the REPLACE WITH field. However, if
     you want to calculate the log of WEIGHT/HEIGHT, you must enter the
     expression as

     =LOG(WEIGHT/HEIGHT)

     since the LOG function is not supported as a database expression
     function. The equal sign signals to the program to use the math
     calculator. For example, if you want to create a field that contains
     the record number, you would use the expression

     =RECNO

     To create a field containing a random number from 0 to 100, you would
     use the expression

     =RAND*100


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     Math Calculator Functions

     Name        Meaning             Example of use
     --------    ----------------------------------
     ABS         Absolute value      ABS(SCORE)
     AVE         Average (Mean)      AVE(LIST))
     ACOS        Arc Cosine          ACOS(SCORE)
     ASIN        Arc Sine            ASIN(SCORE)
     ATAN        Arc Tangent         ATAN(SCORE)
     ATAN2       Arc Tangent y/x     ATAN2(y,x)
     CSC         Cosecant            CSC(SCORE)
     COS         Cosine              COS(SCORE)
     COT         Cotangent           COT(SCORE)
     EXP         Exponentiation      EXP(SCORE)
     INT         Integer             INT(SCORE)
     LN          Natural Log         LN(SCORE)
     LOG         Log base 10         LOG(SCORE)
     MAX         Maximum of list     MAX(1,T2,3)
     MIN         Minimum of list     MIN(1,T2,T3)
     MOD         MOD of number       MOD(9,2) is 9 mod 2
     PI          PI                  PI = 3.14159265358979
     RAND        Random number       number between 0 and 1
     RECNO       Record number       database record number
     RECODE      Recode number       RECODE(SCORE,1,0,1.1,2,2)
     ROUND       Rounds a number     ROUND(1.236,2)=1.24
     SD          Standard Deviation  SD(LIST)
     SEC         Secant              SEC(SCORE)
     SIN         Sine                SIN(SCORE)
     SQRT        Square root         SQRT(SCORE)
     SUM         Sum of list         SUM(1,2,3) = 6
     TAN         Tangent             TAN(SCORE)

     ENTERING & IMPORTING DATA INTO KWIKSTAT

     When you choose the Append records... option from the FILE Menu, you
     will be asked to specify entry from the keyboard or from a file (ASCII
     file). For most small data sets, you will probably enter data from the
     keyboard. If your data is already in another program that supports
     ASCII, dBASE and 1-2-3 type files, you may be able to import the data
     from that program into KWIKSTAT. The following information describes
     how to enter data from the keyboard, from an ASCII file or from other
     programs.

     Once you have opened or created a database, you can enter data from
     the keyboard by choosing the Append Records/from keyboard option from
     the EDIT pull-down menu. When you choose this option, a sub-menu will
     appear allowing you to choose to enter data from the keyboard, from an
     ASCII file or from a DBF file.


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     APPENDING DATA FROM ANOTHER DBASE FILE

     If you have a dBASE file containing data that you want to append to a
     current dBASE file, use the following procedure.

     Note: For this procedure to work, the names of the fields in the two
     databases must be the same. Only fields with the same name will be
     imported.

     Step 1 Open a database: Open a dBASE file by choosing the Open a
     Database option on the FILE Menu.

     Step 2 Choose Data Entry: From the EDIT menu, choose the Append Data,
     from dBASE option.

     Step 3 Specify the name of the dBASE file to read from: Enter the name
     of the dBASE file containing the records you want to append. KWIKSTAT
     will read the data, and will append data from the new database based
     on the fieldnames in the currently opened database.

     Step 4 Verify the import: After appending, you should perform a list
     to verify that the database contains the information you want.

     USING LOTUS 1-2-3 TYPE FILES

     If you have a Lotus 1-2-3 WKS or WK1 file and cannot use the Lotus
     program to translate it, you can use the KWIKSTAT import feature from
     the File Utilities/Import option from the FILE Menu.

     Note: Import will allow you to import a maximum of 128 fields.

     USING COMMA DELIMITED ASCII FILES

     If your program outputs comma delimited ASCII files, that is, there is
     a comma between each field, KWIKSTAT can import this data using the
     "Comma Delimited" option in the File Utilities FILE Menu option.

     The data to be imported can contain numbers and character fields.
     Character fields must be enclosed in quotes "". An example file on
     disk is EXCOMMA.DAT. The first few lines of this file are:

     "A",12,22.3,25.3,28.2,30.6,5,"Text"
     "A",11,22.8,27.5,33.3,35.8,5,"Text"
     "B",12,22.8,30.0,32.8,31.0,4,"Text"
     "A",12,18.5,26.0,29.0,27.9,5,"Text"

     The import procedure looks at the first line of the file to determine
     how many fields to create. This file has 8 fields. The first and last
     are character. The fields will be named VAR1, VAR2, etc. You can
     change these names in the "modify database" option, main menu. The
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     import will attempt to create widths that will allow full storage of
     numbers and text.  Everything after that is automated. Look at the
     file with the List option to verify that the imported data is correct.

     EXPORTING DATA

     You may output the data from your KWIKSTAT (DBF) file into a standard
     ASCII TEXT file. (Often called an SDF file - Standard Data Format
     file.) Outputting the data is useful for transferring your data to
     other programs. Along with the output of data, you may also output a
     "format" file, which describes the contents of the text file. This
     file can be output in "dBASE" style or "SAS" (Statistical Analysis
     System) style. The SAS format could be used in a SAS INPUT statement
     to read the ASCII data file into the SAS program.

     To export data, choose the File Utilities option from the DATA
     pull-down menu to display the KWIKSTAT. From the Utilities menu,
     choose the "Output data to an ASCII file (SDF Standard Data Format)"
     option.

     PRINTING A REPORT

     You may output a listing of the data in the dataset (or a selected
     subset of the database) by using the report facility. To use this
     procedure, choose the "Report: Output data in a report format" option
     after choosing the File Utilities option on the FILE Menu. In this
     procedure you may specify the following report features:

     Which Data Fields To Output
     Output Record Number As A Column
     Title
     Number Of Lines Per Page
     Width Of Page (default is 80)
     Output To A File Or Printer
     Output A Subset Of The Data (search)

     NOTE:You may want to place a coded variable in your data set which
     will allow you to easily select a subset of data to output. Subset
     searches can be:

     1) Exact: case is ignored.

     2) First one or more letters in a field: (AL* matches ALLEN, ALBERT,
     etc)

     3) Keyword: match a letter pattern within a field (i.e., [AL] matches
     ALLEN, BALES, etc).

     The REPORT procedure is menu driven. Simply answer the questions as
     you are prompted. If the report is too wide to fit on a single width
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     of the specified paper width, the report will be printed in parts.

















































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     =====================================
     BASIC STATISTICAL ANALYSIS PROCEDURES
     =====================================

     This section of the KWIKSTAT manual describes the statistical analysis
     procedures available in the BASIC KWIKSTAT edition. The data
     generation and simulations module contains several examples of
     statistical concepts such as a coin flip, sampling from a
     distribution, and confidence intervals.

     USING DESCRIPTIVE STATISTICS

     The Descriptive Statistics module allows you to examine summary
     statistics of the data in a database.

     DETAILED STATISTICS FROM AN EXISTING DATABASE

     This option calculates the mean, standard deviation, median, standard
     error of the mean, minimum, maximum, sum, variance and other
     descriptive statistics for a single variable (field) from a set of
     data.

     If your data is already in a database, perform the analysis using the
     following steps. For example, suppose you want to calculate statistics
     for the TIME1 field in the EXAMPLE database.

     Step 1 Open the database: Choose Open Database from the FILE pull-down
     menu. Select the EXAMPLE database.

     Step 2 Choose Analysis option: Choose the Descriptive Statistics
     option from the ANALYZE menu.

     Step 3 Choose the analysis type: Choose the "Detailed Statistics"
     option from the Descriptive Statistics menu.

     Step 4 Choose the field to analyze: Choose the TIME1 field.

     A screen will appear displaying statistics on that variable.

     DEFINITIONS

     C. I. - Confidence interval - This is a range that describes (with
     some confidence -- usually 95% confidence) where the actual mean of
     the data probably lies. That is, the true mean of the data shown
     above is somewhere between 20.79 and 21.23, with 95% confidence.

     MAXIMUM - The largest number.

     MEAN - A measure of central tendency. The arithmetic average. For
     example if you average the three grades 82, 100 and 88 (82+100+88)/3 =
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     90  -- the average (or mean) is 90.

     MEDIAN - A measure of central tendency. The mean is a statistic such
     that 50% of all numbers in the sample are above the mean and 50% are
     below the mean. For example, in the  list 1, 2, 3, 4, 5 the median
     would be 3.

     MINIMUM - The smallest number.

     MISSING - Reports how many numbers had a missing value code.

     N - How many numbers were used to calculate the statistics.

     PERCENTILES - Tells you what percent of numbers are lower than the
     percentile. For example, the 50th percentile is the median.

     S.E.M. - The Standard Error of the Mean measures the spread of the
     data around the mean value.

     ST. DEV. - Standard Deviation - measure of the spread of the data. It
     is calculated two ways, using n-1 as a divisor and using n as a
     divisor. Usually, most people use the n-1 version.

     SUM - The total of all the numbers added together

     TEST FOR NORMALITY - (Professional edition) - This is a test that the
     data is normally distributed. The test statistic is D. If the p-value
     is < 0.05, there is evidence to assume that the data are NOT normal.

     TUKEY 5 NUMBER SUMMARY - Essentially, the 0th, 25th, 50th 70th and
     100th percentile. See the Hoaglin, et al. reference.

     VARIANCE - A measure of the spread of the data.

     SUMMARY STATISTICS ON A NUMBER OF VARIABLES

     This option allows you to calculate statistics on several variables
     (sample size, mean, standard deviation, minimum, maximum, and standard
     error of the mean). If you have a grouping variable in your database,
     you may request output of summary statistics by group.

     Suppose you want to know the means of all the quantitative variables
     (AGE, TIME1, TIME2, TIME3, TIME4, STATUS) within each of the three
     groups (A, B, C) in the EXAMPLE database. Follow these steps:

     Step 1 Open the database: Choose Open Database from the FILE pull-down
     menu. Select the EXAMPLE database.

     Step 2 Choose Analysis option: Choose the Descriptive Statistics
     option from the ANALYZE menu.
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     Step 3 Choose the analysis type: Choose the "Summary Statistics"
     option from the Descriptive Statistics menu.

     Step 4 Choose the fields to analysis: Select the fields AGE, TIME1,
     TIME2, TIME3, TIME4, then select the "Finish choosing fields" option.

     Step 5 Choose the grouping field: Select STATUS as the grouping field.
     The KWIKSTAT viewer will appear displaying statistics on that
     variable.

     Step 6 Exit the viewer: Then exit the module or perform another
     analysis.

     DETAILED STATISTICS FROM DATA ENTERED BY COUNTS

     If you have a small amount of data or if your data is grouped so that
     you know how many of each number you have (i.e., you have 12  people
     13 years old, 5 people 14 yrs old, 6 people 15 yrs old, etc.) you can
     enter the data at the keyboard. When you choose this option a screen
     will appear allowing you to enter your data. Either enter a single
     value or a value followed by a comma and the number of times that
     number should be used.  For example, entering 34,5 would mean that you
     are entering 5 values of 34. When you enter nothing on a line, this
     signals that you are finished entering the data. A detailed statistics
     screen will appear similar to the one described above.

     APPROXIMATE P-VALUE DETERMINATION

     This option calculates p-values for four test statistics: normal (z),
     student's t, F, chi-square. Enter the statistic, degrees of freedom
     and the calculated value of the statistic, and the program will tell
     you the p-value associated with that statistic.

     To calculate a p-value, follow these steps:

     Step 1 Begin the Descriptive Statistics module: From the main menu
     bar, open the ANALYZE pull-down menu, then choose the Descriptive
     Statistics option.

     Step 2 Choose the p-value option: Select Approximate p-value
     determination.

     Step 3 Enter the p-value information: You will be prompted to enter an
     equation. On the left hand side, designate the test statistic being
     used, i.e., z= , t(df)= , F(dfn,dfd)= , or X(df)=. In parentheses, as
     shown by (df), enter the appropriate degrees of freedom. On the right
     hand side of this equation, enter the calculated value of the
     statistic you wish to know the p-value. For example:

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     t(20)=2

     means you want the two-sided p-value for a calculated t-statistic of
     2.00 with 20 degrees of freedom. In this case, the result is p=0.059.

     Step 4 Exit p-values: To exit the p-value determination procedure,
     enter End.

     STEM AND LEAF DISPLAY

     The Stem and Lead Display is a graph created from a series of numbers.
     The Stem part of the display is the leading digit for the data (such
     as 5 in 54) and the leaf is the trailing digit (such as the 4 in 54).
     When larger numbers are used, the rightmost digits are often ignored.
     For example, if the numbers range from 241 to 845, the stem might be
     the 2 to 8, representing 200 to 800, and the leaf would be 0 to 9,
     representing the 10's. The 1's place would be ignored. KWIKSTAT gives
     you options for choosing the magnitude of the stem and leaf values.

     DESCRIPTIVE AND COMPARATIVE GRAPHS

     The Graphs - Descriptive and Comparative module allows you to create a
     number of different charts and graphs.

     CREATING A BAR, LINE OR AREA CHART

     The Bar/Line Area chart option allows you to create a graph using any
     combination of these kinds of charts. You can also choose other
     options for this graph as discussed later in this section. The
     following two examples show you how to display a bar chart by creating
     a new database using a current database.

     BAR CHART EXAMPLE 1

     Step 1 Create the database: Create the database and enter the data.
     Your database should contain a Label field and a Value field (the
     value field contains the numbers to use for the plot.) You can use the
     "SIMPLE BAR CHART" pre-defined structure when creating a new database
     for this graph. For this example MAGNET is the LABEL field and NAILS
     is the VALUE field.

                 ----These are the fields.-----
           RECORD        LABEL      VALUE
                  ------     ------

     1              SMALL      31    -+
     2              MEDIUM     38     |--- This is the data to plot.
     3              LARGE      51    -+
                      |
                      +----------------- These are the plot labels.
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     Step 2 Enter the Data: Enter the 3 records shown above.

     Step 3 Choose Analysis option: Choose the Graphs option from the
     ANALYZE menu.

     Step 4 Choose the analysis type: Choose the "Bar/Line/Area" option
     from the Graphs menu.

     Step 5 Choose the field to graph: Since there is only one numeric
     field, KWIKSTAT automatically select the Data field.

     The resulting chart contains 3 bars labeled SMALL, MEDIUM & LARGE.
     (You could also use this same data to create a pie chart.

     BAR CHART EXAMPLE 2

     This example will use data already in the database named BARCHART.
     When creating a bar/line/area chart, you can choose more than one
     value field and create a side-by-side bar chart, a stacked bar chart,
     a line chart, an area chart, a point chart, or a chart containing a
     mixture of these types. The data in this example will be used to
     create a chart that includes 2 bars and a line graph.

     Step 1 Open the database: Open the database named BARCHART.

     Step 2 Choose fields: Choose the fields VAR1, VAR2 and VAR 3 as the
     data fields, then choose "Finished Choosing Fields." Select LABEL as
     the label field. A chart will appear containing three side-by-side
     bars.

     Step 3 Choose <options> from the graph menu: An option screen will
     appear that allows you to enter a title, footnote and other options.
     At the bottom of the screen choose <PgDn-Next>. This will display the
     second option screen. See "Options While Displaying a Bar Chart"
     below.

     Step 4 Choose types: For Var3 choose the W (Wide Line) type by
     entering a W in the Type column or by clicking on the option until a W
     appears.

     Step 5 Display plot: Choose (F7-Continue) to display the plot. You can
     use the <get color> option to select whether the bars will use colors
     or tile patterns.

     Your chart can contain any combination of bars, lines, area and point
     charts.

     While displaying a bar chart, you can choose from a number of
     options. Some of these options are:
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     <options> from the menu at the top of the screen, and a two-screen
     option form will appear. On the first screen of the form, you can
     specify the axes labels, footnotes, and whether the bars should be
     stacked.

     Select the <Next> option to display the second screen option form.

     On this form you can specify :

     Legend - For each bar/line etc.

     Type - choose from Bar, Line, Wide Line, Area or Point

     Cumulative - Yes or No

     Color or Patterns - Choose from 14 colors or 10 patterns. Patterns are
     displayed if the Tile option has been chosen from the main graph menu.

     Display Counts - Yes or No

     By clicking on the the Type, Cumulative or Display counts option, the
     options will cycle through the list of options. For Legend, Colors or
     Patterns, enter the desired  or color or pattern number. After making
     changes in the options, display the chart by selecting <<F7 -
     Continue>> option.

     CREATING A PIE CHART: A pie chart is created from a list of counts.
     (See Help)

     CREATING A TIME SERIES/LINE PLOT: A time series plot is useful in
     examining data that are time related, such as profit by month, etc.
     (See Help)

     CREATING AN XY PLOT (SCATTERPLOT): An XY plot (scatterplot) displays
     the relationship between two variables. (See Help)

     PRODUCING A HISTOGRAM: A histogram can be helpful in determining if
     the distribution of a continuous variable is approximated by a normal
     distribution. (See Help)

     DISPLAYING BY-GROUP PLOTS: By Group plots allow you to display graphs
     that show comparisons across groups. (See Help) Types of plots you
     can display in by-group plots include:

     A) Box Plot Comparison
     B) Dot Plot Comparison
     C) Mean and Error Bar Comparison


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     3-D SCATTERPLOT/ SPIN PLOT

     The KWIKSTAT "SPIN" module allows you to interactively view three
     dimensional (XYZ) scatterplots and allows you to  rotate the plot
     along the x, y, or z axes, spin the data, and choose other display
     options.

     CREATING A SPIN PLOT

     The Spin Plot procedure expects your database to contain at least
     three numeric fields and (optionally) a group field. From these
     fields, it can display a three dimensional XYZ plot. For example,
     using the CAR database, follow these steps to create a graph:

     Step 1 Open the database: From the main KWIKSTAT FILE menu, open the
     database named CAR. Or, if you are already in the SPIN module, open
     the database by selecting the "ChooSe a database to open" option.

     Step 2 Begin the Spin module: If you have not already done so, begin
     the Spin plot module by choosing the Spin Plot option from the ANALYZE
     pull-down menu. The Spin Plot  module menu will be displayed.

     Step 3 Select the plot type: From the Spin Plot menu, choose choose
     the "3D XYZ Data visualization plot."

     Step 4 Select the fields to plot: A pick list of fields will appear
     allowing you to choose three data fields, and optionally, choose a
     grouping field. For the CAR database, choose the following fields (in
     this order) MPG, WEIGHT and HP. For the grouping field, choose
     CYLINDERS.

     Note: When a grouping variable is used, the points on the plot will be
     displayed where points for each different group (up to 10 groups) will
     appear in different colors or points for different groups will be
     displayed using a different shaped point (such as a circle, square,
     diamond, etc.) Once you have chosen the fields, an initial plot
     appears.

     Step 5 Spin the Plot: To examine the relationships between the
     variables, spin the plot on one or more axes to view the relationships
     from different angles by pressing an arrow key or PgUp or Pg Dn or
     click on the Spin menu options.

     SPIN PLOT MANIPULATION OPTIONS

     Manually rotate the plot (up-, down-, left- and right-arrow, PgUp and
     PgDn keys) by choosing Roll, Pitch or Yaw. Either point to one of
     these options with the mouse and click, or press the designated
     keyboard button to choose one of these options. Click and hold on a
     spin option and the plot will continue spinning until you let up on
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     the mouse button.

     Automatically spin the plot by pressing CTRL, plus a Roll, Pitch or
     Yaw button (i.e., CTRL-rightarrow). Stop the spinning plot by pressing
     a Roll, Pitch or Yaw button (without CTRL).

     Grow or Shrink: + or -

     Increase or decrease the degree of move: > or <

     USING T-TESTS AND ANOVA PROCEDURES

     T-tests and Analysis of Variance (ANOVA) procedures are used to test
     hypotheses about population means using data obtained through random
     sampling of those populations.

     EXAMPLE: TWO SAMPLE T-TEST (INDEPENDENT GROUPS)

     The data used here are heights of 13 plants grown using two different
     fertilizers.  Suppose you want to know if there is a difference in the
     average heights of plants in the two treatment groups.

     Data for independent group t-test (fertilizer study)

     Present  Newer Fertilizer
     46.2 cm   51.3 cm
     55.6      52.4
     53.3      54.6
     44.8      52.2
     55.4      64.3
     56.0      55.0
     48.9

     Step 1 Create a database: See the tutorial example earlier for
     information on how to enter this data into a database.

     Step 2 Enter the data into the database.

     Step 3 Select the analysis to perform: Choose the t-tests and Analysis
     of Variance (ANOVA) option from the ANALYZE pull-down menu, then
     choose the "Compare independent groups (t-test, ANOVA)."

     Step 4 Select the fields to use: Select GROUP as the grouping variable
     and OBS (Height) as the data (response) variable. The results appear
     on the screen.

     Step 5 Analyze the results: A menu will appear allowing you to view
     the results or display a graphical comparison. Choose to view the
     results. Exit the viewer by choosing F7-Exit.

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     Step 6 View the graphical comparison: Select "Graphical Comparison"
     from the options menu to display a comparison of the results. This is
     the same graph described earlier in the section "Displaying By Group
     Plots." Initially, this plot shows an error bars comparison. Exit the
     viewer by choosing the <Exit> option.

     EXAMPLE: SINGLE FACTOR ANOVA

     When more than two independent groups are compared with respect to one
     variable, one-way or single factor analysis of variance techniques are
     appropriate. This example uses data for hogs which have been randomly
     assigned to four groups, with each group being given a different feed.
     The response is weight gain.

     Data for Independent Group ANOVA

       Gp 1  Gp 2  Gp 3  Gp 4
       60.8  78.7  92.6  86.9
       67.0  77.7  84.1  82.2
       54.6  76.3  90.5  83.7
       61.7  79.8        90.3

     The database to analyze this data is similar to the one used for the
     t-test example  above, differing only with respect to the number of
     groups. In fact, this one-way ANOVA is an extension of the t-test when
     there are three or more groups. To perform this analysis, use these
     steps:

     Step 1 Create or Open a database: Create a database using the "FOR
     INDEPENDENT GROUP T-TEST OR ANOVA" pre-defined structure. GROUP will
     be the grouping field. The groups will be numbered 1,2,3,4 according
     to the type of feed used. The response field will be OBS. Or, open the
     database named HOG, and skip to step 3.

     Step 2 Enter the data: The data, as entered into the database will
     look like this:














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     RECNO  GROUP  OBS (WEIGHT)
     1        1    60.8
     2        1    67.0
     3        1    54.6
     4        1    61.7
     5        2    78.7
     6        2    77.7
     7        2    76.3
     8        2    79.8
     9        3    92.6
     10       3    84.1
     11       3    90.5
     12       4    86.9
     13       4    82.2
     14       4    83.7
     15       4    90.3

     Step 3 Select the analysis to perform: Choose the t-tests and Analysis
     of Variance (ANOVA) option from the ANALYZE pull-down menu, then
     choose the "Compare independent groups (t-test, ANOVA)."

     Step 4 Select the fields to use: Select GROUP as the grouping field
     and OBS (Weight) as the response variable. The results appear on the
     screen.

     Step 5 Analyze the results: The results of this test are summarized in
     the p-value. In this case, the small p-value (p<<0.001) means that
     there is a significant difference between groups. This is taken as
     evidence of a "real" difference between feeds, a difference not due to
     chance.

     The ANOVA tells you only that there is a difference among the feeds.
     In order to find out which groups are significantly different from
     which others, examine the multiple comparison results. The
     Newman-Keuls multiple comparison test (or whichever you specified at
     setup) will describe which of the means are significantly different
     from which others (at the 0.05 significance level). One part of the
     output is the multiple comparison test. The test performed depends on
     what option you chose during setup. This example will describe the
     results of the Newman-Keuls test. The results of this test are as
     follows:

         Gp  Gp  Gp  Gp
          1   2   4   3
                 -------
        ----
             ----

     The group numbers are given in increasing order of the value of their
     group means. That is, Group 1 has the smallest mean, Group 3 the
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     largest. At the 0.05 significance level, the means of any two groups
     underscored by the same line are not significantly different. This
     display tells you that (at the 0.05 significance level):

     1) The mean for group 1 (feed 1) is statistically significantly less
     than the means for all other groups.

     2) The mean for group 2 (feed 2) is significantly greater than the
     mean for group 1, and significantly less than the means of groups 4
     and 3.

     3) The means for groups 4 and 3 are not significantly different from
     each other, but they are both significantly greater than the means of
     groups 1 and 2.

     You can conclude that feeds 3 and 4 are better than feeds 1 and 2, but
     there is not enough evidence to say that either feed 3 or 4 is the
     best overall.

     Step 6 View the graphical comparison: Select "Graphical Comparisons"
     from the options menu to display a graphical comparison of the
     results. This is the same graph described earlier in the section "By
     Group Plots."  Initially, this plot shows a comparison using error
     bars. This figure shows a box plot comparison. From this plot you can
     visually see that groups 3 and 4 are similar and that group 1 is much
     lower than the rest. Exit the viewer by choosing the <Exit> option.

     PARAMETRIC REPEATED MEASURES (PAIRED) ANALYSIS

     Repeated measures are observations taken on the same or related
     subjects over time or in differing circumstances. Examples would be
     weight loss, or reaction to a drug across time.

     EXAMPLE PAIRED T-TEST

     The data in this example are before and after weights for eight
     persons on a diet. Notice that in this case, both data values are
     taken from the SAME entity (person). Follow these steps to perform
     this analysis:

     Step 1 Create or Open the database: Use the pre-defined database
     structure named "FOR PAIRED T-TEST OR McNEMAR's TEST." This will
     create a database with the fields REP1 and REP2. The REP1 will be used
     for Before and REP2 will be used for After. Or, open the database
     named DIET, and skip to step 3. Data for paired t-test





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     Person  Before After
     1       162    168
     2       170    136
     3       184    147
     4       164    159
     5       172    143
     6       176    161
     7       159    143
     8       170    145

     Step 2 Enter the data: Enter the data for the eight records. The
     database should look similar to the listing of the data above.

     Step 3 Choose the analysis: Choose the t-tests and Analysis of
     Variance (ANOVA) option from the ANALYZE pull-down menu. Then choose
     the "Compare repeated or paired data (t-test, ANOVA)" option from the
     module menu.

     Step 4 Select the fields to use: Select REP1 (BEFORE) as the first
     field and REP2 as the second field.

     Step 5 Analyze the results: Choose to View the results from the
     options menu. Select "Graphical Comparisons" from the options menu to
     display a graphical comparison of the results.

     EXAMPLE ONE-WAY REPEATED MEASURES ANOVA

     For more than a pair of repeated measures on the same subject, a
     one-way repeated measures analysis of variance is appropriate. The
     data in this example are repeated measures of reaction times of five
     persons after being treated with four drugs in randomized order.

     One-way repeated measures ANOVA data

     Person  Drug 1  Drug 2  Drug 3  Drug 4
     1        31      29      17      35
     2        15      17      11      23
     3        25      21      19      31
     4        35      35      21      45
     5        27      27      15      31

     The results of this ANOVA are summarized in the p-value. In this case,
     the small p-value (The (p=)0.000 on the "Repeated Factor" line in the
     ANOVA table.) means that there is a statistically significant
     difference in the mean response times for the four drugs.

     The Newman-Keuls multiple comparison test (or whichever multiple
     comparison test you chose at setup) describes which of the means are
     significantly different from which others (at the 0.05 significance
     level). See previous ANOVA example.
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     SINGLE SAMPLE ANALYSIS

     This option allows you to choose a single variable, and test a
     hypothesis that the mean differs from an hypothesized mean. You must
     enter the hypothesized population mean.

     DUNNETT'S TEST

     Dunnett's test is a multiple comparison procedure following a one-way
     ANOVA that compares a control mean with the other means in the
     analysis.

     NON-PARAMETRIC PROCEDURES

     Non-parametric procedures are appropriate when the assumption of
     normality cannot be made for a small data set or when a large data set
     is known to be from a non-normal population. Non-parametric procedures
     are generally based on ranks rather than actual data values, so these
     procedures can be useful also when actual data values are not known,
     but the order or ranks of the data values are known.

     MANN-WHITNEY PROCEDURE

     If two independent groups, such as in this example, are being
     compared, the Mann-Whitney U-statistic is calculated.

     EXAMPLE: MANN-WHITNEY TEST OF TWO INDEPENDENT GROUPS

     The fertilizer data from the t-test example are used in this example.
     If you have not already created the database for this data set, do so
     now by referring to that example. Follow these steps to do this
     example:

     Step 1 Open the database: Open the database named FERTILIZ and choose
     the Non-Parametric Comparisons option from the ANALYZE menu. Or, if
     you are already in the Non-Parametric module, select the "ChooSe a
     Database" option and open the FERTILIZ database.

     Step 2 Select analysis type: From the Non-Parametrics Comparisons menu
     select "Independent groups - Mann-Whitney, Kruskal-Wallis."

     Step 3 Select fields to use:  Choose GROUP as the grouping variable
     and OBS (HEIGHT) as the data (response) variable.

     Step 4 View the results: KWIKSTAT will display the results, including
     the Mann-Whitney U statistic, the rank sums, sample sizes and mean
     ranks of the groups, a z statistic and an approximate p-value. In this
     case, U'=24.00, U = 16, z=0.357 and p=0.721.

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     The p-value of 0.721 is large so the null hypothesis of no difference
     in medians between groups is not rejected. There is not sufficient
     evidence based on this procedure to say that there is a difference
     between the median heights of plants in the two groups grown using
     different fertilizers.

     KRUSKAL-WALLIS PROCEDURE

     If more than two independent groups are being compared using
     non-parametric methods, KWIKSTAT uses the Kruskal-Wallis test. The
     database used is of the same form as for the one-way independent
     gropu analysis of variance.

     KWIKSTAT will display the Kruskal-Wallis H-statistic, the rank sums,
     sample sizes and mean ranks of the groups, a chi-square statistic and
     an approximate p-value, and a graph of the results similar to the
     one described for the one-way ANOVA.

     NON-PARAMETRIC REPEATED MEASURES ANALYSIS -  FRIEDMAN'S TEST

     When repeated observations are taken on the same subject, and there is
     interest in comparing the observations for each repeated measure
     (e.g., each type of treatment), then a repeated measures analysis may
     be appropriate. Data for Friedman's test is the same as described in
     the one-way repeated measures ANOVA. The results include a multiple
     comparison of groups.

     NON-PARAMETRIC DICHOTOMOUS DATA ANALYSIS - COCHRAN'S Q

     Cochran's Q procedure is a non-parametric procedure appropriate for
     use with dichotomous data when the experiment involves repeated
     measures on blocks. The response of the subjects to the treatments is
     dichotomous if it is taken as one of only two possible outcomes, often
     labeled "success" and "failure", rather than as a measurement.

     USING REGRESSION & CORRELATION PROCEDURES

     To examine the linear relationship between variables, correlation and
     linear regression are used.

     SIMPLE LINEAR REGRESSION ANALYSIS

     Data for this example of simple linear regression are Homicide Rate
     and Handgun Licenses Issued per 100,000 population for the years 1961
     to 1973 in Detroit (Fisher, 1976, reprinted from Gunst and Mason,
     1980).




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     Data for simple linear regression (handgun study)

     Year  Homicide  Handguns
            Rate    Registered
     1961   8.60     178.15
     1962   8.90     156.41
     1963   8.52     198.02
     1964   8.89     222.10
     1965  13.07     301.92
     1966  14.57     391.22
     1967  21.36     665.56
     1968  28.03    1131.21
     1969  31.49     837.60
     1970  37.39     794.90
     1971  46.26     817.74
     1972  47.24     583.17
     1973  52.33     709.59

     Since you want to compare the homicide rate with handguns registered,
     you need a database with only these two sets of numbers (you can
     exclude year.) The data for this example is stored on your disk as
     HANDGUNS.DBF with the variables HOMICIDES and HANDGUNS.  See chapter 2
     if you need information about how to create a database. To perform a
     simple linear regression using this data, follow these steps:

     Step 1 Open the database: Open the database named HANDGUNS. If you are
     at the main menu, select the Open a Database option from the FILE
     menu, then choose Regression and Correlation from the ANALYZE menu. If
     you are in the Regression module, select "ChooSe a Database."

     Step 2 Select analysis type: From the Regression menu, choose the
     "Simple Linear Regression" option.

     Step 3 Select the fields to use: Select HOM_RATE as the DEPENDENT (Y)
     variable first, then select HAND_REG as the INDEPENDENT (X) variable.

     Step 4 View the results: KWIKSTAT will perform calculations and
     display a menu. Choose "View/Print Results," which will display
     information as shown in figure 4.21. Exit the viewer with F7/Exit.

     Step 5 View the Plots: View a scatterplot of the original data with
     the fitted regression line, and a plot of the residual values by
     choosing "Display Plot" items from the options menu.

     Step 6 Forecast new values: You may optionally want to predict new
     values from the calculated regression line. If so, choose that option,
     and enter the number or range of numbers of the Independent variable
     you want to use to predict.

     Pearson's correlation coefficient (r) is reported (0.7263) as well as
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     R2 (R-Square, 0.5275). The linear regression equation given is a
     mathematical representation of a straight line that passes through a
     plot of the data, and can be used to predict the dependent variable
     (HOMICIDES) given a value for the independent variable (HANDGUNS). In
     this case the linear regression equation is:

     HOMICIDES = 4.910512 + 3.761144E-02 * HANDGUNS

     If you want to predict the homicide rate for 300 handguns registered,
     you would use the equation:

     HOMICIDES = 4.910512 + 3.761144E-02 * 300

     A t-test is performed to test the statistical significance of the
     linear relationship between the two variables. A low p-value means
     that the two variables are significantly related.

     Regression Plots: These plots are helpful to determine if a linear fit
     to the data is appropriate. The scatterplot shows you how compact or
     spread apart the points are around the fitted lines, and may help you
     discover outliers. The residual plot helps you determine if a linear
     fit is appropriate.

     Predicting new values: When you choose this option, you will be
     prompted for one or more X variable values for which you wish to
     predict Y variable values.

     MULTIPLE REGRESSION ANALYSIS

     Multiple regression is an extension of simple linear regression into
     several dimensions (several independent variables). In the multiple
     regression procedure, you must enter a list of the independent
     variables and a single dependent variable on which you wish to perform
     the regression analysis. In KWIKSTAT you may use up to 10 independent
     variables in this option. Multiple regression can be complicated.

     KWIKSTAT calculates and displays several results, including the
     coefficients and intercept of the regression "line". A significance
     test is performed to determine the significance of the contribution of
     the different variables or factors to the model (mathematical
     representation).

     EXAMPLE MULTIPLE REGRESSION ANALYSIS (LONGLEY DATA)

     Longley introduced a data set which has often been used in comparing
     multiple linear regression procedures in the literature. The variables
     refer to economic factors.  This example uses the LONGLEY database on
     the KWIKSTAT disk. Follow these steps to perform a multiple linear
     regression:

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     Step 1 Open the database: Open the database named LONGLEY. If you are
     at the main menu, select the Open a Database option from the FILE
     menu, then choose Regression and Correlation from the ANALYZE menu. If
     you are in the Regression module, select "ChooSe a Database."

     Step 2 Select analysis type: From the Regression menu, choose the
     "Multiple Linear Regression" option.

     Step 3 Select the fields to use: The LONGLEY database consists of 7
     fields: DEFLATOR, GNP, UNEMP, ARMED, POP, TIME, and TOTAL. The first
     six of these will be used as independent variables and the seventh,
     TOTAL, is the dependent variable (the one to be predicted). Select
     TOTAL as the DEPENDENT variable and DEFLATOR, GNP, UNEMP, ARMED, POP,
     TIME as the INDEPENDENT variables, then select "Finished Choosing
     Fields."

     Step 4 View the results: KWIKSTAT will perform calculations and
     display the results as shown in figure 4.22

     The table at the top of the output (in Figure 4.22) tells you the
     intercept value and the coefficient values for each of the independent
     variables. These can be used to create an equation for prediction of
     the dependent variable.

     In this case, the equation is:

     TOTAL = -3481930.1065 + DEFLATOR*(15.0161517122) +
     GNP*(-0.03579443400) + UNEMP*(-2.0199053296) + ARMED*(-1.0332049046) +
     POP*(-0.05130725587) + TIME*(1828.99249535)

     Note: Although the results are reported to 8 to 9 decimal places, it
     is usually not appropriate or necessary to use this many decimal
     places. After viewing or printing the results, exit the viewer.

     Step 5 View the Plots: From the options menu, you can choose to view
     residual plots to determine if the data are linear. If the residual
     plots do not show random patterns, you should determine if there is a
     transformation you can perform on the data to make it linear.

     Step 6 Forecast new values: From the options menu, you can choose to
     predict new values from the calculated regression line.

     KWIKSTAT also reports R-Square, which gives you a measure of how well
     the regression "line" fits the data.

     It is a good idea to view plots of residuals. The plots are helpful to
     determine if regression analysis is appropriate. A pattern other than
     a random horizontal band about zero indicates that the assumptions
     necessary for a regression procedure may be violated.

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     CORRELATION ANALYSIS

     The correlation coefficient is a measure of the strength of the linear
     relationship between two variables. KWIKSTAT allows you to find both
     Pearson's and Spearman's (rank) correlation coefficients of two
     variables. It also displays the matrix of correlation coefficients of
     pairs of variables when there are more than two variables being
     considered.

     This example uses the Longley data described in the Multiple
     Regression example above. To display the correlation matrix, use these
     steps:

     Step 1 Open the database: Open the database named LONGLEY.

     Step 2 Select analysis type: From the Regression menu, choose the
     "Correlation Matrix" option.

     Step 3 Select the fields to use: The LONGLEY database consists of 7
     fields: DEFLATOR, GNP, UNEMP, ARMED, POP, TIME, and TOTAL. Select all
     the fields for this analysis. KWIKSTAT will perform the calculations
     and display a 7 by 7 matrix.

     Only half of the array is displayed since the other half is a mirror
     image. The diagonal entries are also omitted since they are all one; a
     variable is always perfectly correlated with itself.

     Each entry in the array consists of two numbers (three numbers if the
     information is printed to a printer). The first (upper) is the
     Pearson's correlation coefficient for the two (row and column)
     variables of that entry. The second (middle) number, in parentheses,
     is the p-value of the t-test for Ho: rho = 0 vs. Ha: rho <> 0. In the
     hard copy printout (if requested), the third (bottom) number, in
     brackets, is the sample size, or number of paired observations used in
     the calculations.

     EXAMPLE GRAPHICAL CORRELATION MATRIX (LONGLEY DATA)

     This example uses the Longley data used in the previous example. To
     perform this analysis follow these steps:

     Step 1 Open the database: Open the database named LONGLEY.

     Step 2 Select analysis type: From the Regression menu, choose the
     "Graphical Correlation Matrix" option.

     Step 3 Select the fields to use: The LONGLEY database consists of 7
     fields: DEFLATOR, GNP, UNEMP, ARMED, POP, TIME, and TOTAL. Select all
     the fields for this analysis. KWIKSTAT will perform the calculations
     and display the scatterplots.
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     These scatterplots are a visual way of examining the relationships
     between pairs of variables. It allows you to determine if a
     relationship exists between the variables, and allows you to see if
     that relationship is linear. You can use this graphical correlation
     matrix to examine the relationships between variables before using
     them in a multiple regression analysis.

     USING FREQUENCY AND CROSSTABULATION PROCEDURES

     The Crosstabulations, Frequencies, Chi Square module performs analyses
     on categorical data, that is, data observed in categories, rather than
     measurement data.

     EXAMPLE: FREQUENCY TABLE, BAR AND PIE CHARTS

     This example uses the EXAMPLE database file. One of the fields
     (variables) in this database is STATUS referring to socioeconomic
     status. Suppose you want to know how the total data set is divided up
     into the five levels of STATUS. You also want to produce a visual
     display of this information. To perform this analysis follow these
     steps:

     Step 1 Open the database: Open the database named EXAMPLE, then
     choose the Crosstabulations, Frequencies, Chi Square option from the
     ANALYZE menu. If you are already in the Crosstabulations, Frequencies,
     Chi Square module, select the "ChooSe Database" option.

     Step 2 Choose the analysis type: Select the "Frequencies" option from
     the Crosstabulations, Frequencies, Chi Square module menu .

     Step 3 Select field: You will be prompted to select one field
     (variable) to use. Since you want to do a frequency table on STATUS,
     select STATUS from the field list.

     Step 4 View results: When you choose to view/print the results, a
     frequency table is displayed as shown in figure 4.26. Exit the viewer
     with F7.

     If you select "Pie Chart," a pie chart, as described earlier in this
     chapter (Graph Module) will be displayed. If you choose "Bar Chart," a
     bar chart as described earlier in this chapter will appear.








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     PERFORMING A GOODNESS OF FIT ANALYSIS

     A goodness-of-fit test of a single population is a test to determine
     if the distribution of observed frequencies in the sample data closely
     matches the expected number of occurrences under a hypothetical
     distribution of the population.

     According to a genetic theory, crossbred pea plants show a 9:3:3:1
     ratio of yellow smooth, yellow wrinkled, green smooth, green wrinkled
     offspring. Out of 250 plants, under the theoretical ratio
     (distribution) of 9:3:3:1, you would expect about

     (9/16)x250=140.625   yellow smooth peas,
     (3/16)x250=46.875    yellow wrinkled peas
     (3/16)x250=46.875   green smooth peas
     (1/16)x250=15.625  green wrinkled peas

     After growing 250 of these pea plants, you observe that

     152 have yellow smooth peas
       39 have yellow wrinkled peas
       53 have green smooth peas
         6 have green wrinkled peas

     To perform this analysis, use the following steps:

     Step 1 Select the analysis type: From the Crosstabulations,
     Frequencies, Chi Square menu choose the "Goodness-of-Fit" option.

     Step 2 Enter the data: You will be prompted to enter the number of
     categories. In this case, type 4 for the four categories of peas
     (yellow smooth, yellow wrinkled, green smooth, green wrinkled) and
     press Enter. You will also be asked if you want to enter the expected
     ratios, or if you will be entering the actual expected values into the
     table. If you choose to enter ratios, you will enter

     9,3,3,1

     An empty table will appear with the instructions to enter the observed
     values for each category. Enter the observed values given above,
     pressing Enter after each entry. For example, for the first row, enter
     152 for observed (Press Enter) enter 39 (Press Enter) and so on.
     KWIKSTAT will perform the calculations (including filling in the
     expected values column) and display the results.

     The calculated chi-square statistic in this case is 8.97 and the
     p-value is 0.031. At a 0.05 level of significance, this p-value
     indicates that there is enough evidence to reject the null hypothesis
     that the observed values follow the theoretical distribution. That is,
     the test (at the 0.05 significance level) suggests that a 9:3:3:1
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     ratio of yellow smooth:yellow wrinkled:green smooth:green wrinkled
     peas is not an appropriate distribution for the population from which
     these data are taken.

     PERFORMING A CROSSTABULATION ANALYSIS (CHI-SQUARE)

     Crosstabulations can be used to perform a chi-square test for
     independence or a chi-square test for homogeneity. A two-way table is
     constructed that displays the number of counts for each category.
     Crosstabulation table options you may choose for constructing a table
     include:

     A) Frequencies only
     B) Include Expected Values
     C) Include Expected Values and Percents
     D) Include Expected Values, Chi-Contribution and Percents
     E) Include Percents
     F) Include Expected Values and Chi-Contribution
     Q) Quit this option

     EXAMPLE: 2 BY 2 CROSSTABULATION TEST FOR INDEPENDENCE

     Data for this example are observations of the number of beetles and
     bugs on the upper and lower sides of leaves (Zar,1974, page 292).

     2 by 2 Contingency Table Data

                Beetles  Bugs
                 ---------------
     Upper Leaf   12      7

     Lower Leaf   2       8

     Since you are given only the totals for each of the four categories,
     and not the individual data for each leaf, there is no need to create
     a database. Rather, you can just enter these totals from the keyboard.
     To perform this analysis, follow these steps:

     Step 1 Choose analysis type: From the Crosstabulations, Frequencies,
     Chi Square menu, select the "Crosstabulations, Chi-Square" option. You
     will be asked if you want to "Read data from the database" or "Enter
     data from the keyboard." For this example, select "K" to enter data
     from the keyboard.

     Step 2 Select size of table: You will then be prompted to give the
     size of the table. When asked for the number of rows, type 2 and press
     Enter. When asked for the number of columns, again type 2 and press
     Enter. An empty table will appear with the instructions to enter the
     counts for each category into the appropriate cell.

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     Step 3 Enter the data: Enter the values given above, pressing Enter
     after each entry. KWIKSTAT will perform the calculations and display
     the results.

     The calculated chi-square statistic in this case is 4.89 with a
     p-value of 0.028. The chi-square with Yates correction is 3.31 with a
     p-value of 0.069 and the Fisher Exact Test (two tail) has a p-value of
     0.050. Because one of the cells produces an expected value less than
     5, KWIKSTAT gives a warning that the chi-square analysis for this data
     may not be valid. Given this warning, it is best to rely on the
     Fisher's Exact Test for making a decision.

     EXAMPLE: ANALYZING A LARGER TABLE (SEX BY HAIR COLOR)

     A generalization of the 2 by 2 table is the R by C (Rows by Columns)
     table. This is an example (Zar, 1984, page 62) of a two by four
     contingency table involving the variables hair color and sex. The null
     hypothesis is that there is no relationship between hair color and
     sex.

     2 by 4 Contingency Table Data (sex by hair color)

                HAIR COLOR
           Sex        Black  Brown  Blonde  Red
         -----------------------------------------
           Male        32     43     16      9
           Female      55     65     64     16

     Since you are given only the totals for each of the eight categories,
     and not the individual data for each person, there is no need to
     create a database. Rather, you can just enter these totals from the
     keyboard. To perform this analysis, follow these steps:

     Step 1 Choose analysis type: From the Crosstabulations, Frequencies,
     Chi Square menu, select the "Crosstabulations, Chi-Square" option. You
     will be asked if you want to enter data from a (D)atabase or
     (K)eyboard. Type K and press Enter.

     Step 2 Select size of table: You will then be prompted to give the
     size of the table. When asked for the number of rows, enter 2. When
     asked for the number of columns,  enter 4. An empty table will appear
     with the instructions to enter the counts for each category into the
     appropriate cell.

     Step 3 Enter the data: Enter the values given above, pressing Enter
     after each entry. KWIKSTAT will perform the calculations and display
     the results.

     Step 4 Analyze the results: The calculated chi-square statistic in
     this case is 8.99 with a p-value of 0.03. A decision can be made using
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     this p-value of the test. A low p-value (less than the chosen
     significance level) is usually taken to indicate rejection of the null
     hypothesis.

     CREATING A 3-D BAR CHART

     As an option when performing a Crosstabulation, KWIKSTAT allows you to
     draw a 3-dimensional bar chart of data for a contingency table
     (crosstabulation), and then to focus in on a part of it if desired.
     Data for the 3-dimensional bar chart must be entered first, either
     from the keyboard or a database, by using the "Crosstabulations,
     Chi-Square" option.

     MCNEMAR'S TEST

     McNemar's test is appropriate for use with paired, dichotomous data.
     This test is sometimes called a test for related samples or a test for
     the significance of changes. It is useful for comparing paired or
     related observations in which the response is dichotomous, that is,
     the response is one of only two possible outcomes. McNemar's test is
     the 2 by 2 version of Cochran's Q test described in the section on
     non-parametric tests. The test assumes that any pair of observations
     is independent of any other pair of observations, although clearly the
     observations within a pair are not independent of each other.

     LIFE TABLES AND SURVIVAL ANALYSIS

     Survival Analysis is used to analyze the survival experience of a
     group of persons or components. In medical research, survival analysis
     is helpful is studying the survival of patients under one or more
     conditions. In industry, the survival may be that of a component such
     as an electronic switch or a gear. To perform a survival analysis, the
     data must be in the following form:

     1) a TIME variable which contains a time (e.g., minutes, days, years,
     etc.) in which the subject or component has been observed to be alive
     (not failed).

     2) a CENSOR variable which must take on the values 0 or 1,  where 1
     means the subject has died (failed), and a 0 means the subject was
     still alive (not failed) at the last available time period.

     3) optionally, a GROUPING variable which may have up to ten values
     (numeric or character), i.e., the data may be in groups.

     KWIKSTAT allows you to choose from two types of life tables, Actuarial
     or Kaplan-Meier. The Actuarial method uses fixed length intervals in
     the table, and the Kaplan-Meier table uses intervals based on the
     data.

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     Once the data are entered into the program, a life table for each
     group is produced which includes, for each time interval, the number
     entered, withdrawn, lost, dead, exposed, the proportion dead,
     proportion surviving, cumulative proportion surviving, and other
     information.

     A plot is given for the cumulative proportion surviving in the
     group(s) against time. If more than one group is entered, a
     Mantel-Haenszel log-rank test is performed to test the hypothesis of
     equal survival patterns for the groups. A reference to how this test
     is developed is covered in Matthews and Farewell (1988).

     EXAMPLE: ACTUARIAL LIFE TABLE ANALYSIS

     The data for this example are in the LIFE database on the KWIKSTAT
     disk. These data are from Prentice (1973). To perform this analysis,
     follow these steps:

     Step 1 Open the database: If you are at the main KWIKSTAT menu, choose
     the Open Database option from the FILE menu and select the database
     LIFE, then choose the Life Table and Survival Analysis option from the
     ANALYZE menu. If you are already in the Life module, open the LIFE
     database by selecting the "ChooSe database to open" option.

     Step 2 Choose the analysis type: Select the "Actuarial Life Table
     Analysis" option from the Life Table and Survival Analysis menu. Step
     3 Choose fields to use: The LIFE database consists of 3 fields:
     SURVIVAL, CENSOR, and GROUP. A portion of the LIFE database is shown
     here:

     SURVIVAL  CENSOR  GROUP
     72         1       1
     411        1       1
     228        1       1
     11         1       1
     25         0       1
     144        1       1
     etc...

     The first column is the SURVIVAL field with entries of length of life,
     or length of survival. The second column is the CENSOR field, an
     indicator of whether the subject has failed (died) or not at the last
     observed time period. 1 means failed, 0 means not failed (still
     alive).

     The third column contains a grouping variable. In this case it is
     either 1 or 2. Group 1 may represent one treatment, while group 2
     represents another kind of treatment. The objective is to compute
     survival curves to see if the treatments provide different average
     survival distributions.
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     Select SURVIVAL as the TIME variable, CENSOR as the censor variable
     and GROUP as the grouping variable.

     Step 4 Select interval length: KWIKSTAT reports the names and sizes of
     the groups and then asks you to specify the length of each interval
     for the table to be produced. You can specify a desired interval
     length or you can use the default length by simply pressing Enter. For
     this example, press Enter to select the default length.

     Step 5 Analyze the results: KWIKSTAT will perform the calculations and
     display an options menu. If you choose the View/Print option two sets
     of tables, one for each group will be displayed. The first table
     includes the numbers of subjects entered alive, withdrawn, dead,
     exposed, the proportion dead, proportion alive, cumulative survival
     proportion and standard error for the first group. The second table
     includes 95% confidence limits on the cumulative survival proportion.

     From the table, you can see that, in the first group, 22 of 37
     exposed, or 59.5% died in the first interval (0.0-99.0) and two were
     withdrawn. In the second group, 12 of 23.5 exposed (51.1%) died and
     one was withdrawn in the first interval. Exit the viewer by selecting
     F7/Exit.

     Comparing Survival Curves: At the end of the report, KWIKSTAT reports
     the results of the Mantel-Haenszel comparison of the two curves. The
     hypotheses being tested are:

     Ho: The survival curves are the same.
     Ha: The survival curves are not the same.

     In this example, the Mantel-Haenszel comparison procedure results in a
     chi-square statistic of 0.7191 and a p-value of 0.397. This p-value is
     much too large to reject the hypothesis of equal curves. This
     indicates that the two distributions are not statistically
     significantly different - thus neither treatment is superior in terms
     of survival distributions.

     Displaying Survival Curves: From the options menu, you can choose to
     display survival curves. This is a graphical representation of the
     cumulative proportion surviving from the life table. The survival
     curve for this analysis is shown.

     The Kaplan-Meier life table contains most of the same information as
     the Actuarial Life Table. However, instead of the time intervals being
     fixed, the time intervals are based on time values from the data.




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     ==========
     REFERENCES
     ==========

     Box, Jenkins, and Reinsel, Time Series Analysis - Forecasting and
     Control, Prentice-Hall, 1994.

     Deming, W.E., Out of Crisis, Cambridge, MA:  Massachusetts Institute
     of Technology, Center for Advanced Engineering Study, 1986

     Dixon, W.J. and Massey, F.J., Introduction to Statistical Analysis,
     McGraw-Hill Book Company, New York, 1969.

     Elliott, A.C. and Woodward, W.A.,"Analysis of an Unbalanced Two-Way
     ANOVA on the Microcomputer", Communications in Statistics, Volume B15,
     Number 1, 1986.

     Gunst, R.F., and Mason, R.L., Regression Analysis and its
     Applications, Marcel Dekker, New York, 1980.

     Granger, C.W.J. and Newbold, P., Forecasting Economic Time Series,
     Academic Press, 1977.

     Hoaglin, D.C., Mosteller, F., Tukey, J.W., Understanding Robust and
     Exploratory Data Analysis, John Wiley & Sons, Inc. New York, 1983.
     (Box and Whiskers Plots, Stem and Leaf Displays)

     Kennedy, W. J., Jr., and Gentle, J.E., Statistical Computing, Marcel
     Dekker, Inc, New York, 1980.

     Larsen, R.J. and Marx, M.L., Statistics, Prentice-Hall, 1990.

     Lehmann, E.L. Nonparametrics: Statistical Methods Based on Ranks,
     Holden-Day, Inc, Oakland, Ca, 1975.

     Longley, J.W. "An appraisal of least squares programs for the electronic
     computer from the point of view of the user." JASA, 1967, 62, 819-831.

     Montgomery, D.C., Introduction to Statistical Quality Control, John
     Wiley and Sons, 1991.

     Neter, J., Wasserman, W., and Kutner, M. H., Applied Linear
     Statistical Models, Richard D. Irwin, Inc., 1990, Third Edition.

     Prentice, R.L. "Exponential survivals with censoring and explanatory
     variables.", Biometrika 60, 1973, 279-288.

     Ryan, Thomas P. Statistical Methods for Quality Improvement, John
     Wiley & Sons, New York, 1989. Tukey, J.W., Exploratory Data Analysis,
     Addison-Wesley, 1977.
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     Tsay, R.S., and Tiao, G.C., "Consistent Estimates of Autoregressive
     Parameters and Extended Sample Autocorrelation Functions for
     Stationary and Nonstationary ARMA Models," JASA 79, 84-96, 1981.

     Winer, B.J., Statistical Principles in Experimental Design, Second
     Edition, McGraw-Hill Book Company, 1971.

     Woodward, W.A., Elliott, A.C., Gray, H.L and Matlock, D.C., Directory
     of Statistical Microcomputer Software, Marcel Dekker, New York, 1988.

     Woodward, W.A., and Gray, H.L., "On the relationship between the
     S-array and the Box-Jenkins Method of ARMA Model Identification," JASA
     76, 579-587, 1981.

     Zar, J.H., Biostatistical Analysis, Prentice Hall, Inc, 1974 and 1984
     editions.

































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     ===========
     APPENDIX A
     ===========
     INTERPRETING ERROR CODES

     While every precaution is taken in writing software, all possibilities
     of use cannot be anticipated. If the program encounters a problem it
     does not know how to resolve, it will usually display an error
     message. This message will contain an error code and a reference code.
     If you encounter an error message, write it down and refer to this
     list to see if you can figure out how to resolve the problem. If you
     are unable to resolve the problem, please write down the steps you
     took before the error was encountered, and send it to TexaSoft on the
     Problem Report Form. We will try to resolve the problem as quickly as
     possible.

     Error Number 5 = Illegal function call
     Error Number 6 = Overflow
     Error Number 7 = Out of Memory
     Error Number 9 = Subscript out of range
     Error Number 11 = Division by zero
     Error Number 14 = Out of String Space
     Error Number 24 = Device Timeout
     Error Number 25 = Device fault
     Error Number 27 = Out of Paper
     Error Number 50 = FIELD overflow
     Error Number 51 = Internal Error
     Error Number 52 = Bad filename or number
     Error Number 53 = File not found
     Error Number 54 = Bad file mode
     Error Number 55 = File already open
     Error Number 57 = Device I/O error
     Error Number 58 = File already exists
     Error Number 61 = Disk full
     Error Number 62 = Input past end of file
     Error Number 63 = Bad record number
     Error Number 64 = Bad filename
     Error Number 67 = Too many files
     Error Number 68 = Device unavailable
     Error Number 70 = Permission denied
     Error Number 71 = Disk not ready
     Error Number 72 = Disk media error
     Error Number 74 = Rename across disks
     Error Number 75 = Path/File access error
     Error Number 76 = Path not found
     Error Number 81 = Invalid filename




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     PROBLEM REPORT FORM: KWIKSTAT

     Please explain in detail the problem that occurred. If possible, send
     a printout of the results or Print Screen if possible.

     KWIKSTAT VERSION#_____________ RELEASE#________________
     (see opening screen)
     KWIKSTAT module where problem occurred:______________________
     (It is often helpful if you can indicate the precise commands you
     used leading up to the problem.)
     Your computer brand/model_____________________________________
     (Also indicate if it is a 8088, 286, 386, 486, Pentium)
     Monitor type: (circle one) EGA, or VGA (including SuperVGA)
     Amount of free memory available:____________________
     (use the MEM or CHKDSK command to find this out.)
     Version of DOS you are using:____________________________________
     (Use the VER command to find this out.)
     Memory resident program in use:__________________________________
     Running KWIKSTAT from (i.e DOS, Windows, DOS SHELL):__________
     PROBLEM:

















     Mail to:TexaSoft, P.O. Box 1169, Cedar Hill, Texas 75106-1169. Or fax to
     214-291-3400, or send E-Mail to Compuserve 70721,3145 or Internet
     [e-mail].










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     KWIKSTAT 4.1 Statistical Data Analysis
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     USER'S BALLOT

     Please indicate your preference for improvements in KWIKSTAT. On a
     scale of 0 to 10

     0 = Very Low priority for this change
     10 = Very High priority for this change

     Vote  Proposed item of change
     ----  ---------------------------------------------------------
     ____  Windows version
     ____  Add more ANOVA types - example:___________
     ____  Add more Non-parametric statistical tests
     ____  Add General Linear Model
     ____  Make Report more flexible
     ____  Add more Quality Control options
     ____  Cluster Analysis
     ____  Discriminant Analysis
     ____  Add other types of analysis - example:__________
     ____ _____________________________________________
     ____  _____________________________________________
     ____  _____________________________________________
     ____  _____________________________________________
     Other Comments:(Your ideas are very important us.)








     Mail to:TexaSoft, P.O. Box 1169, Cedar Hill, Texas 75106-1169. Fax
     to:214-291-3400 or send E-Mail to Compuserve 70721,3145 or Internet
     [e-mail].


















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