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TexaSoft's
USING KWIKSTAT 3.3 (Condensed Manual)
(C)Copyright 1991,1992 Alan C. Elliott
Winner of the 1992
SIA Award for
"Best Math or Enginnering Program"
For additional information on this product, contact TexaSoft, P.O. Box
1169, Cedar Hill, Texas 75104 (214) 291-2115, Fax: (214) 291-3400,
Compuserve:70721,3145.
ACKNOWLEDGEMENTS
This manual was written by Alan Elliott and Marcia Stoesz.
ALL RIGHTS RESERVED
Note:There is important information in the file LATENEWS.DOC. To view
this file enter the command TXVIEW LATENEWS.DOC. The file is on disk 3
in the 5.25 inch version.
NOTE:TO PRINT AN ORDER FORM, CHOOSE THE "ABOUT" OPTION IN THE HELP
MENU, YOU WILL BE GIVEN THE OPTION TO PRINT AN ORDER FORM. OR, PRINT
THE FILE NAMED KSORDER.TXT.
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PART I AN OVERVIEW OF KWIKSTAT
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.
WHY USE KWIKSTAT?
KWIKSTAT can help you:
1. decide the appropriate data analysis procedure to use,
2. enter data or use data already in popular formats such as dBASE,
1-2-3 or ASCII,
3. provide a complete analysis in one pass so the user does not have
to run multiple programs to perform a single analysis, and
4. provide interpretations of the results to assist the user in making
decisions based on the outcomes of the analyses.
KWIKSTAT REQUIREMENTS
KWIKSTAT is designed to run on IBM PC and 100% compatible computers
including the IBM PS/2 computers. It requires PC-DOS or MS-DOS version
3.0 or higher. Your computer should contain at least 364K or more of
free RAM memory. KWIKSTAT graphics require a CGA, EGA, VGA or Hercules
compatible monitor. Many printers are supported. A mouse is optional.
INSTALLATION
To install on a hard disk, place the KWIKSTAT distribution disk in the
A: drive and enter the command A:INSTALL and follow the instructions
on the screen. To use KWIKSTAT on a two-disk 360K machine, place
disk three (3) in the A: drive and type the command FTIPS.
NOTE:This manual is a condensed version of the printed and illustrated
version of the manual you receive when you register. Please ignore
references to figures.
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USING THE KWIKSTAT MENU
Once you installed and setup KWIKSTAT, to begin the program, enter the
the KS command from the DOS prompt.
The main menu contains three options, Data, Analyze and Helps. Using
the right and left arrow keys on the cursor pad, you can move the menu
selection to one of the other two menu bar options. Pressing the right
arrow key once, moves the menu bar option from Data to Analyze. The
Data pull-down menu vanishes and the Analyze pull-down menu appears.
Pressing the left arrow key moves the selection back to the Data 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 on the cursor pad 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.
USING THE ANALYZE MENU
The KWIKSTAT Analyze menu allows you to choose which analysis module
to run. Usually, you first open a database in the Data menu, then
choose one of the options in the Analyze menu. For example, to
calculate descriptive statistics on information in the EXAMPLE
database, first open the EXAMPLE database by choosing Open a database
to use in the Data menu and selecting EXAMPLE from the database list.
Then press the right arrow key once to open the Analyze pull-down
menu. Then choose the Descriptive Statistics and Graphs option from
the Analyze menu. This begins the Descriptive Statistics and Graphics
module, which contains a menu of procedure options.
USING THE KWIKSTAT HELP SYSTEM
The KWIKSTAT Help system contains two levels of help. From the "Helps"
pull-down menu, you can choose the Help On Using The Program option
or the Decide What Analysis To Use Option. Other options on this menu
are About Kwikstat, which gives copyright information about the
program and allows you to print an order form. The GO to DOS, Return
with Exit (Shell) option allows you to temporarily return to the DOS
prompt. The Change Setup option allows you to setup KWIKSTAT fror your
computer.
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TUTORIAL:TRY THIS EXAMPLE
This short tutorial will give you a feeling for how to use KWIKSTAT. It
is not intended to be thorough, but simply to lead you though a common
procedure. It will assume you are using KWIKSTAT on a hard disk. To begin
KWIKSTAT, you must first be in the \KWIKSTAT directory on your hard disk.
Use the CD (Change Directory) command from the DOS prompt to change to
the \KWIKSTAT directory by using the command:
CD\KWIKSTAT
Once in the \KWIKSTAT directory, begin KWIKSTAT with the KS command:
KS
The Data menu that should appear is the same as was illustrated
previously in Figure 1.1. (If the Analyze menu appears, press the left
arrow key once to open the Data menu.) The Data pull-down menu is
extended, as described above in the section "Using the KWIKSTAT Menu
System".
ACCESSING THE KWIKSTAT HELP SCREENS
To examine the KWIKSTAT HELP menu, press the F1 function key. You can
think about the HELP procedure as a book, with screens instead of
pages. It is really a condensation of the manual. The KWIKSTAT Program
Help screen menu was illustrated in Figure 1.3. To look at a
particular topic, enter the screen number you desire. For example,
look at screen 7. Type the number 7, and press Enter:
Enter SCREEN NUMBER or Enter to Cancel:7 (You enter the 7.)
If you enter a 7, KWIKSTAT displays screen 7. (If you press Enter without
first typing a number, the Help is canceled, and you will return to the
menu.) Once you have displayed screen 7, to move to screen number 8,
press Enter. To go back to the menu, type the "M" key. To exit the HELP
module, press the Enter key from the main Help menu or the Esc key from a
help screen. Press Enter now. This takes you back to the KWIKSTAT Data
pull-down menu. Every module has the help screens available.
The KWIKSTAT "Decision" help screen is available from the Helps pull-down
menu. To decide what kind of descriptive analysis to use for a single
variable, choose help screen option 1 by typing a 1, then press Enter.
A screen describing descriptive analysis options is displayed (as in
Figure 1.5). For example, if your data is near normal (quantitative),
use the B (detailed statistics), C (summary statistics) and/or E
(histogram) options in the Statistics module. Pressing Esc will end
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the help system and return you to the main menu.
EXAMPLE OF DESCRIPTIVE STATISTICS
This example will use data already stored in a dBASE ".DBF" file
named EXAMPLE currently on the KWIKSTAT disk. To open this database,
extend the Data pull-down menu. Then select the Open a Database
option. A "PICK" menu will appear. That is, a list of database names
will be displayed, and you can pick one of the names from this menu.
Choose the EXAMPLE database. (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.
Press the "L" key once to choose the List the Contents of a database
option from the menu. This will list the contents of EXAMPLE database to
the screen. Press Enter several times to list the entire database to the
screen. When the list is finished, you will return to the Data pull-down
menu.
Extend the Analyze pull-down menu. Choose the Descriptive Statistics
and Graphs option from the Analyze menu. KWIKSTAT now switches to the
Descriptive module (which may take a few seconds). Soon, you will see
the Descriptive Statistics menu, as illustrated in Figure 1.6.
From the Descriptive Statistics menu, choose Detailed statistics on a
single variable. The program now displays the variables available for
analysis from the database.
Choose variable number 2, "AGE". Before the statistics for this
variable are displayed, two options are presented. First, you are
prompted you with the question:
Specify Confidence Interval level (.5 to .99)
(Default is .95)
For this example, press Enter to accept the default, which tells the
program to display a 95% confidence interval for the data on the
statistics screen. Next, a second option appears with the prompt:
Default for percentiles is Tukey 5 Number Summary
Specify your own percentiles to calculate < yes > < No >
When a Yes/No question appears on the screen, notice that the Y or the
N will be uppercase. This means that if you press Enter without
entering a Y or an N, the uppercase option is the default (No). For
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this example, to choose No to the question, just press Enter. Or point
to No with the mouse and click. The program will now perform a series
of calculations on the data, and will produce a screen of descriptive
statistics, and a box plot of the data. The results are illustrated in
Figure 1.8.
Notice that this screen is different from previous screens. The
information on this screen is displayed in graphics mode (if you have a
graphics monitor). Normally, information on the screen is in "text" mode.
If you are using a color monitor, a text mode screen will display text in
the colors you selected in the setup procedure. When graphs are displayed
on the screen, the program must use a graphics screen mode. In graphics
mode, some graphs appear only in black and white, although some graphs
will appear in color. On all graphic screens in KWIKSTAT, a menu will
appear at the bottom of the screen for a few seconds, then disappear.
This allows you to capture or print the screen without the menu appearing
on your printout. To bring the menu back, press the spacebar once. The
menu options are still available even when the menu is not visible. The
menus differ according to your setup and particular options available for
the graphic display, but most graphic menus will include the following
options:
Esc:ExitR:Replot P:Print
That is, press Esc to end the display, press R to replot (choose other
display options) and P to print the graphic screen to the printer.
Depending on your monitor setting, the menu may also contain a "Capture
PCX" option. This option allows you to capture the graphic screen into a
PCX type file that you can then use in other programs such as WordPerfect
or Pagemaker.
If you want a printed copy of this graphics screen, MAKE SURE YOUR
PRINTER IS TURNED ON, and is ON LINE, and HAS PAPER. Then, press "P"
(for Print).
To return to the main Descriptives menu, press the Esc key. To end this
module and return to the main KWIKSTAT menu, press Esc. To end KWIKSTAT
from the main menu, press Esc again and answer Y to the prompt "End
KWIKSTAT."
This ends the tutorial. All of the procedures are explained more fully
later in the manual. However, you may find that after finishing this
tutorial, you will be able to use most of the KWIKSTAT features
without any further aid from the manual.
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Part II
Using the KWIKSTAT Database
The KWIKSTAT DATA pull-down menu in the main KWIKSTAT module is used
to manage your data. From this menu you enter data, change data,
create new data fields from existing ones, and perform other data
maintenance tasks. Once your data is in the KWIKSTAT (dBASE-type)
database, you can access the data from any of the other KWIKSTAT
modules.
Some of the KWIKSTAT procedures require that you have data in a file
before you can do an analysis. Other procedures allow you to enter
information from the keyboard at the time you request the procedure.
Some procedures give you an option to enter data from a database, or
from the keyboard.
HOW DATA IS STORED IN KWIKSTAT
A KWIKSTAT database uses the same file format as the dBASE III and dBASE
IV programs. Therefore, data already stored in a dBASE III or dBASE IV
file may be read directly into all the KWIKSTAT programs. The only
exception to this is that KWIKSTAT does not read dBASE MEMO fields.
Therefore, if your data in dBASE contains memo fields, you may have to
create a subset of your database before using it in KWIKSTAT. Data from
other programs can also be used in KWIKSTAT. Refer to the section called
"Entering Data into the Database."
The menu for the data options appears as the DATA option on the main
KWIKSTAT menu. The following information describes how to use the options
in this menu to create, manipulate and modify a database for use in
KWIKSTAT.
The Open a database to use option on the DATA 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. Use this option to choose the
database that you will be analyzing.
When you choose the OPEN option on the DATA menu, a list of databases
currently in the default directory will be displayed, as shown in Figure
2.2. To select a database, use the up and down arrow keys to highlight
a database name, then press Enter. Or, point to the entry with the
mouse pointer and click.
If the database you want to use is not in the current (default)
directory, you can temporarily change the default directory by
pressing the F2 function key. Once a database is open, you will see
its name at the bottom left of the screen, along with the number of
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records in the database. You can edit, pack, modify, set missing
values, subset and list the database using the other options on the
DATA menu.
DESIGNING AND CREATING A DATABASE
The Create a new database option on the DATA menu is used to create a
new database. The structure, or layout, of a database must be
described before you enter your data. You need to give some thought
to how your database will "look" so it will be in the proper format to
do the analysis you desire. In the descriptions of statistical
procedures (Part IV), specific examples are given about how a database
should be constructed for a particular type of analysis.
Kwikstat allows you to create a new database in two ways:
1. Choose from a predefined structure or
2. Create a customized database
Both of these options are discussed in the sections below.
USING A PREDEFINED DATABASE STRUCTURE
You can choose to create a custom database structure (which was the
only choice for version 3.0 and earlier) or you can choose from a list
of pre-defined databases that are designed for specific analyses. The
list below contains examples of some of the pre-defined database
descriptions. For example, if you need to enter data for an
independent group t-test, you would choose the option called "For
independent group t-test or ANOVA." The proper database structure for
this analysis will be created and then you can enter your data into
the database.
DEFINE THE FIELDS IN YOUR DATABASE
When you first enter the definition mode, the blinking cursor will be
in the FIELD NAME area. Enter a name, (must begin with a letter, can
contain letters, numbers and "_" (underscore) and may be up to 10
characters long) and press the ENTER key. The name you choose will be
displayed in all capital letters, and the cursor will move to the next
area, TYPE.
In the TYPE area, you only need to enter the first character of the
type (N, C, L or D), - Numeric, Character, Logical or Date, then
press the ENTER key.
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WIDTH is the number of characters reserved for the entry. Decimal is
the number of decimal places (only for numbers). Note that the number
of decimal places must be at least one less than the width. For
example, if a number has the format ###.##, the width is 6 (count the
decimal point), and the number of decimal places is 2. If DATE or
LOGICAL is entered as type, the program will automatically assign a
width of 8 or 1 respectively.
Unless your database is big, you might make each field one more
character wide that you actually need. This provides for
unanticipated large numbers and facilitates data entry.
Once a complete field description is entered, a next blank field
description will appear, ready for entry. To end the creation process,
type Ctrl-END (^END). As long as you have not ended the procedure, you
may use the cursor keys to back up, and make any corrections. If you
mess up, end the procedure with Esc and begin again. When you press
^End, the following message appears.
Enter Records (data) into the database now
<yes> <No>
If you want to enter data now, answer "Y" to the question. Otherwise
answer "N". You can always enter the data later.
LIMITATIONS TO THE KWIKSTAT DATABASE
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 AND ANALYSIS EXAMPLES
This section provides you with two examples of using Kwikstat. Please 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.
The first example shows you how to create a custom database and calculate
some simple statistics and a graph. The second example shows you hot to
use a pre-defined database structure to perform a t-test.
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EXAMPLE 1
DESCRIPTIVE STATISTICS EXAMPLE
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.
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
16 A 18 F 140 24.5
17 B 16 F 101 23.6
18 A 21 F 111 20.0
19 B 17 F 124 21.9
20 B 18 M 176 21.5
Before performing any kind of analysis on this data, you must first enter
it into a Kwikstat database. The process is:
1. Create a database
2. Enter the data
3. Perform an analysis
These processes will be explained in the next few sections.
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CREATE A DATABASE
When you begin the Kwikstat program, the main Kwikstat menu appears.
If you have not yet created the database, you must choose the Create a
new database option, which will lead you through the steps in creating
a database. This section describes that procedure.
Note: Once a database has been created, you can use the data in it
again by choosing "Open a database to use" from the Data menu. When
you choose Create a new database from the Data menu, you will then be
prompted to enter the name of the database, as shown in figure 2.6.
You need to enter a name for the database that is a DOS compatible
file name such as MYDATA.
Once you have entered a filename for the database, you can choose from
a list of pre-defined database structures, or create your own. In this
example, you will create your own database structure. From the menu
shown in figure 2.7, choose the CREATE A CUSTOMIZED DATABASE
option. For each field (each item of data) in the database, you must
specify a fieldname, a type a width and optionally the number of
decimal places. 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". Notice that the widths defined here
are actually 1 character wider than actually needed. If you are not
pressed for space in the database, this will make your listings easier
to read. Only the SCORE variable requires a decimal value. Enter the
information about the database structure into the database definition
screen (see the section,"Define the Fields in Your Database" above) as
shown in figure 2.9.
When you will be prompted with the question,
Enter records (data) into the database now?
Type a Y to begin entering records into the database.
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ENTER THE DATA
When you choose to enter the data in a new database, an 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 screen, 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 either
screen.
TIP: You can toggle between spreadsheet entry mode and database entry
mode by pressing the F8 (Switch) key.
USING A SPREADSHEET ENTRY SCREEN
The spreadsheet screen, as shown in figure 2.10 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). 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, you can use the Edit mode (described later) to correct
this entry. When you have finished entering the information in the
database, your screen will look like figure 2.11.
To end the entry procedure, press the F7 (Exit) key. A message will
appear on the screen:
Before exiting, do you want to save the
record number 21
<yes> <No>
Answer No to this question since you do not want to have a blank record
in your database.
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CORRECTING ERRORS IN THE DATABASE
Before returning to the main menu, you can correct errors by pressing 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 with the F7 (Exit) command.
If you end up with an extra record in your database, you can erase that
record while in the Edit mode. To erase a record, place your cursor on
the record and press F4 (Erase). The record will be permanently removed
from the database. Exit the edit screen with the F7 (Exit) command.
USING A DATABASE ENTRY SCREEN
This section describes how to enter data using the database entry mode.
When you begin entering data into a new database, an entry screen for
record 1 appears on the screen similar to figure 2.12. (Information for
record 1 already entered).
The database entry screen displays each field name at the left of the
screen followed by an entry field where you will enter the data for that
field. For example, when the entry screen first appears, your cursor will
be in the GRADE field. To enter the information for record 1, type the
grade value for the first record, A (upper case) and press Enter. Your
cursor will move to the next field. Type 18 and press Enter. Continue
until you have entered 22.3 in the SCORE field. When you press Enter
after entering 22.3, a new entry screen appears for record 2 to allow you
to enter the second record of information, and you cursor moves to the
first field of this record. Continue entering information until all
records are entered. If you make a mistake on a record, you can use the
arrow keys to move your cursor and correct the mistake. If you discover
that you have made an error in a previous record, you can use the Edit
mode (described later) to correct this entry.
ENTRY AND EDIT SCREEN FUNCTION KEY COMMANDS
When you are adding 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. To choose an option, press the function key
related to the option, or point to the option with the mouse and click.
F1 - Displays the Kwikstat Help menu.
F2 - Toggles between edit mode and append mode.
F3 - Marks a record for deletion. (Same as ^U.) Also undeletes
records.
F4 - Erase the current record permanently from the
database. (Only in spreadsheet entry mode.)
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F5 - Goto a record number.
F6 - Undo - returns last record changed to it previous values.
F7 - Exits entry mode and returns you to the main Kwikstat menu.
F8 - Switches between spreadsheet type entry and database entry mode.
F9 - Insert or Delete a field in the database or Replace the
contents ofa field.
F10 - Prints the contents of the current record to a printer or file.
PERFORMING AN ANALYSIS
Once you have entered your data into the database, you are ready to
perform one or more analyses. Exit the data entry mode by pressing the
F7 - Exit key. You will return to the Kwikstat main menu. All of the
Kwikstat analysis procedures are listed in the Analyze menu. With the
Kwikstat main menu displayed, you can press the right or left arrow
key to pull-down the Analyze menu.
For the MYDATA database you have just created, you will calculate some
summary statistics and display a graph. The sections below lead you
through these procedures.
CALCULATING SUMMARY STATISTICS
From the Analyze menu on the main Kwikstat menu screen, choose the
Descriptive Statistics and Graphs option. A new menu will appear
containing the options for the Descriptive Statistics and Graphs
program module.
The Descriptive Statistics and Graphs menu, lists the statistics and
graphs you can produce from information in the current database. For
example, suppose you want to calculate summary statistics for all of
the numeric variables in your database. To do this, select the option
called Summary Statistics on a number of variables. A screen will
appear prompting you to specify what fields to use in the
calculations. A list of the variables in the database appears. Enter
the field numbers for each variable you want included in the analysis,
separating each variable number with a comma. For example, if you want
to choose variables 2 (AGE), 4 (WT) and 5 (SCORE), enter
2,4,5
at the prompt, as shown at the Enter: prompt in figure 2.15 and press
Enter.
Once you select the variables to use, you are asked if there is a
grouping variable.
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Enter a grouping variable by number or Enter for none:
A grouping variable allows you to calculate summary statistics by
group, such as SEX. You could enter a 3 at this prompt to specify that
you want the summary statistics broken down by SEX, but for this
example, simply press Enter to specify no grouping variable. The next
question asks you if you want to
Choose (C)ontinue (F)ile (P)rint or (R)eturn to menu:
To continue with the calculation and display the results on the
screen, just press Enter. When you do, the summary statistics for the
selected variables will appear on the screen. Once you have examined
these results, press Enter to return to the Descriptive Statistics and
Graphs menu.
Example 2
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. The
example uses the spreadsheet entry type. The data used in this example
is the same as in example 4.7 in the manual (page 4-23 and following.)
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 were observed. The results are:
Data for independent group t-test (fertilizer study)
Present Newer
Fertilizer 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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CREATING THE DATABASE AND ENTERING DATA
Since the observations are independent, the database will include
thirteen records (one for each plant) and two fields (one for the
response and one for the group indicator).
Choose to create a database named TTEST. 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 For 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 (where you will enter a 1 or 2,
the fertilizer type) and an observation field (where you will enter
the height.)
Once you have selected a database type, you will be asked if you want
to enter records now. Answer Yes.
Enter the data into the database. 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. Figure 2.21 shows a screen where all 13
records have been entered, and the program is waiting for a 14th
record to be entered.
Since there is no 14th record, press the F7 function key (Exit) to end
the data entry process. You will be prompted with the question, Do you
want to save the record number 14?" You do not want to save this blank
record, so answer N (No). KWIKSTAT will return to the Data main menu.
PERFORMING THE ANALYSIS
Once you have entered the data into a database, and you are back at
the main menu, select the Analyze option at the top of the main
Kwikstat menu screen. When the Analyze pull-down menu appears, select
the t-tests and Analysis of Variance (ANOVA) option.
When you choose the t-tests and Analysis of Variance (ANOVA) from the
Analyze menu, the menu shown in figure 2.23 will appear. Select
Compare independent groups (t-test, ANOVA). You will be prompted to
choose the field name of the group, which in this case is simply
GROUP. Choose GROUP. Next, you will be asked for the data field.
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Choose OBS (HEIGHT), the response variable. KWIKSTAT will now perform
the calculations and display the results on the screen.
Refer to the section "Using t-tests and ANOVA Procedures" in Part IV
of this manual for information on interpreting this information. When
the results screen is displayed, typing G will cause a graphical
comparison of the two samples. First, a screen containing Tukey's five
number summaries (listing the 0, 25, 50, 75, and 100 percentiles for
each group) appears. Press Enter, and box plots for each group will
appear as shown. Press Esc to exit from the box plots. You will be
given the option to print a report for this analysis. If you choose
this option, a summary of the analysis will be printed to the printer
or to a file. After you have printed the report (or chosen not to
print the report), you will return to the module menu. To return to
the main Kwikstat menu, press Esc. To end the program and return to
DOS, choose the F option, Quit to DOS.
ENTERING DATA INTO THE DATABASE
When you choose the Data entry option from the DATA 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 another program supports ASCII, dBASE and 1-2-3 type
files, you may be able to enter data from that program in to KWIKSTAT.
The following information describes how to enter data from the
keyboard, from an ASCII file or from other programs.
ENTERING DATA FROM THE KEYBOARD
If you choose KEYBOARD data entry, an entry screen will appear
containing the fields you created in the CREATE option. This entry
screen will either use the database or spreadsheet format mode,
depending on which one you specified when you chose setup options.
However, you can easily toggle from one entry mode to another by
pressing the F8 key. Examples 1 and 2 above describe these two entry
methods.
ENTERING DATA FROM AN ASCII FILE
When you choose to enter data from an ASCII file, you will be asked
the name of the raw data file. (i.e., \MYDIR\MYDATA.DAT). The data
from the ASCII file will be entered into the database, and a count of
the records as they are entered will be displayed. If there are
already records in the file, the new data from the ASCII file will be
appended (added) as new records to the database. It is a good idea to
go to the List procedure to look at the data to verify that it has
been entered correctly, or print the data out using the report option
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(See Using KWIKSTAT Utilities). If the data does not match the fields,
refigure the widths of each field to make sure it matches the columns
of data in the disk file, and try again.
KWIKSTAT can read data from standard ASCII text files. These kinds of
files are usually supported by most word processing programs (such as
WordPerfect DOS Text Mode) as well as most text editors such as EDLIN.
Data must be in the form of column data, like this...
A 22 3.3 WF
A 33 4.2 BF
B 27 3.3 WM
:
ETC
Notice that each column of data is in fixed fields. It does not matter
that there is no space between the last two fields (Race and Sex)
since the program will pick off the information from the column and
does not require that there be spaces between the columns. Use the
instructions below to prepare the KWIKSTAT (dBASE) database structure
to be used to read in ASCII data.
The steps to enter ASCII data into KWIKSTAT are:
STEP 1. Use the CREATE option to create a database structure to match the
columns in the ASCII file. The field widths MUST match the width of the
columns of data on file. If there are spaces between columns of data,
make widths wide enough to account for those spaces. The following data
is from the file EX.DAT on disk:
A 12 22.3 25.3 28.2 30.6 5
A 11 22.8 27.5 33.3 35.8 5
B 12 22.8 30.0 32.8 31.0 4
A 12 18.5 26.0 29.0 27.9 5
B 9 19.5 25.0 25.3 26.6 5
:
etc
:
B 12 22.4 27.2 31.8 35.6 4
Try your hand at doing this example by creating a database named EX with
the following structure:
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FIELD NAME TYPE WIDTH DECIMALS
----------- ------ ------- --------
GROUP C 2
AGE N 4 0
TIME1 N 5 1
TIME2 N 5 1
TIME3 N 5 1
TIME4 N 5 1
STATUS N 2
Notice that even though the first column has data 1 column wide, this
structure uses a width of 2 for GROUP. Even though the age only uses 2
columns, the structure calls for AGE to have a width of 4. These
widths are enter this way to take care of the blank spaces between the
columns. If GROUP had been set up with only 1 column and AGE with only
2 columns, the ASCII data would not be read into the database
correctly. Create the database called EX with the specifications
listed above, then go to the next step.
NOTE: KWIKSTAT can also produce an ASCII text file, so that data
created in KWIKSTAT can be output, and read into other programs.
STEP 3: To verify that the data was read properly, use List option on
the DATA menu to examine the resulting database.
ENTERING DATA FROM ANOTHER PROGRAM
KWIKSTAT was designed to read dBASE, comma delimited ASCII and 1-2-3
files because these are among the most commonly used types of files to
store data. See information on the utility module later in this
manual.
EDITING, DELETING AND PACKING DATA
Once a database is created, you often need to correct information by
editing records or getting rid of records. The following sections
describe the process of changing the contents of a record by editing and
a procedure for getting rid of records by deleting and packing.
EDITING RECORDS
If there is a need to change data already in a database, you may choose
the Edit a record option from the DATA menu. You will be asked to specify
the record number you wish to edit. Editing is similar to entering data.
Use the up and down arrow keys to move from field to field within a
record. See the Examples above for a tutorial on editing information in
a database.
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DELETING RECORDS
If you want to delete an entire record within a database, use the edit
procedure to display the record to delete.
You can use one of two methods to delete a record:
1. Erase the record (Spreadsheet mode only) or
2. Delete and Pack
To erase a record, display the record in Edit mode, using the spreadsheet
entry mode. Highlight the record to erase, and press the function key F4.
If you want to delete more than a few records, it will probably be more
efficient to use the Delete and Pack method. While a record is displayed
(either in spreadsheet or database edit mode), press ^U to mark the
record for deletion. A **DEL** will appear on the screen (upper right
corner) of a "deleted" record (database mode) or a "*" will appear next
to the field name (spreadsheet mode). You can mark as many records as you
choose. If you accidentally mark a record for delete, pressing ^U a
second time will cancel the mark, and the **DEL** will disappear from the
screen. Once you have marked the records for delete, pack the database,
as described below.
TIP:If you want to temporarily "get rid" of a few records so that they
will not be used in an analysis, mark them for delete. Any analysis you
perform will ignore deleted records. Then, if you want to restore them,
unmark them again. This is a quick way to see how an analysis result
would change if some selected records were not present in the analysis.
PACKING THE DATABASE
The records marked for delete are not actually deleted 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. You can undelete
records from the Edit mode.
If you want to permanently get rid of the records you have marked for
delete, choose the Pack procedure from the Data menu. This procedure
erases all "deleted" records from the database.
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MODIFYING AND DISPLAYING THE STRUCTURE
The Modify or Display database structure option on the DATA 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 field, you age given a chance to the modify
the characteristics of that 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 option
from the Data menu.
SETTING 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.
A standard dBASE III file does not have a way to designate missing
values, but KWIKSTAT allows a way for you to designate these values in
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this program. The Indicate missing value codes option on the DATA 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.
IMPORTANT NOTE: If missing values are NOT used, and there is a blank
numeric variable in a calculation, it will 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 will be in error!!
CREATING A NEW FIELD
In previous versions of Kwikstat, to create a new variable, you chose
the Transformation option. This option only allowed the creation of
numeric variables. This option have been replaced by a procedure in
the Edit mode, which allows you to create new blank fields of any
field type, and to place information in those fields that is either a
numeric or character expression. Thus, this procedure replaces the old
Transformation procedure. The sections "Create a New Field" and
"Replacing the Contents of a Field" describe these procedures. 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 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).
CAREFUL ATTENTION must be paid to the definition to assure that the
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calculated numbers will fit into the field width specifications. If the
calculated number is too large to fit into the field, it will be given
the missing value code. If an illegal calculation is attempted, such as a
division by 0, the result will be missing. If a calculation includes a
missing value, the result will be a missing values.
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 CONTENTS OF A FIELD
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 RATIO
with the values WEIGHT/HEIGHT:
1) 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.
2) Specify which records to replace. The default it 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 number 1 through 20. Then, press
Enter.
3) Specify what to place in the field. For example, enter the formula
WEIGHT/HEIGHT in the Replace With entry field, where WEIGHT and HEIGHT
are two other fields in the same database.
4) Specify any 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 AGE20 in the
condition entry field.
5) 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. An example of the Replace dialog box is shown in figure
2.28.
The kinds of expressions you can use the Replace With and Condition
fields are described below.
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KWIKSTAT supports two kinds of expressions. One is strictly for
mathematical expressions, called a math expression. Thhe other expression
type, called a database expression, allows the use of character, numeric,
date and logical fields in the expression. Here are the criteria for when
these are used:
REPLACE WITH FIELD: Use either a math expression or a database
expression.
CONDITION FIELD: Use only a database expression.
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 two expression types are in 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 experssion
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. The information below outlines the capabilities of both
expression types.
Mathematical operators supported are Add +, Subtract -, Divide
/, Multiply *, and Exponentiation ^ (Math calculator 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
=SCORE^2 (= signals math calculator)
LTRIM(FIRST)+' '+LAST
Note: Literal strings included in expressions must be surrounded by
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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 TIP:Unless you use scientific functions in your
calculations, you don't need to be concerned about which calculation
type to use. Only if you use a numeric operation or function not
supported by the database calculator will you need to place an equal
(=) sign at the first of the expression.
Database calculator functions supported The following functions may be
used in expressions both in the Replace With and Condition
fields.
Database Calculator Functions
ABS(NUM), ASC(STG), AT(STG1,STG2), CALENDAR(NUM), CAPS(STG), CHR(NUM),
DATE(), DELETED(), IIF(LEXP,AEXP1,AEXP2), INT(NUM), JULIAN(DATE),
LEFT(STG,NUM), LEN(STG), LOWER(STG), LTRIM(STG), MAX(NUM1,NUM2),
MIN(NUM1,NUM2), RECNO(), REPLICATE(STG,NUM), RIGHT(STG,NUM),
RTRIM(STG), SPACE(NUM), STR(NUM), STRING(NUM,NUM|STR), RIGHT(STG,NUM),
STUFF(STG,NUM,NUM,STG2), SUBSTR(STG,NUM,[NUM]), TIME(), TRIM(STG),
UPPER(STG), VAL(STG),
Following a few example uses of these functions:
ASC - Converts the first character of a string to its ASCII code. For
example, the function ASC('A') would return the value 65, since 65 is
the code for an uppercase A.
AT - Returns the starting position of one character string within
another character string. For example, the expression AT('Bill', 'Wild
Bill') = 5 since the string 'Bill' begins five characters deep in the
string 'Wild Bill'.
CHR - Converts a number into its ASCII value. For example, CHR(65) is
equal to the character string 'A'.
DELETED - Returns a T if the current record is marked for delete, else
it returns a F. Can be used to conditionally replace a value depending
on if the record is deleted or not.
INT - Rounds down to nearest integer. INT(3.2) would be returned as 3.
LEFT and RIGHT - Returns the left or right portion of a string. For
example, LEFT('Wild Bill',3) would return the string 'Wil' and
RIGHT('Wild Bill',3) would return the string 'ill'.
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LOWER and UPPER - Returns lower or upper case string. For example,
LOWER('Wild Bill') would return 'WILD BILL'.
LTRIM, RTRIM and TRIM - Trims blanks from right, left or both ends of
a string. For example, LTRIM('Wild Bill ') would return 'Wild
Bill'.
VAL - Returns the value of a string. For example VAL('24') is the number
24.
Most of these functions are similar to or identical to functions used in
the BASIC language or in dBASE or other database programs. For more
examples, you might refer to documentation on these programs.
MATH EXPRESSIONS
The following functions are supported only in the Replace With entry
field, and only for numeric field types. You MUST preceed expressions
using these functions with an = sign.
An example of the RECODE function, which appears on the following table
is:
=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 fields 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.
Math Calculator Functions
ABS(NUM), ASIN(NUM), ATAN(NUM), ATAN2(y,x), CSC(NUM), COS(NUM),
COT(NUM), EXP(NUM), INT(NUM), LN(NUM), LOG(NUM), MAX(1,T2,3)
MIN(1,T2,T3), MOD(NUM1,NUM2), PI, RAND, RECNO,
RECODE(NUM1,NUM2,NUM3,NUM4,NUM5,NUM6), ROUND(NUM,DEC), SEC(NUM),
SIN(NUM), SQRT(NUM), SUM(NUM1,NUM2...), TAN(NUM),
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SUBSETTING THE DATABASE
The Subset database option on the DATA menu allows you to create a new
database from an old database. 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.
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 DATA 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:
= > < >= <= <> =
and the logical operators .NOT., .AND., and .OR..
It is important that a dot (.) appear before and after each
logical operator. For example, you might enter a condition such as
AGE <10 .OR. SEX='M'
When you choose the Subset option from the Data 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. Example of subsetting
criteria are:
GROUP = 4
GROUP> STATUS
GROUP < WEIGHT*HEIGHT
TIME1 = TIME2*1.96
SEX = 'F'
TIME1 <=20 .AND. SEX = 'M'
When creating these expressions, you can use the same functions as was
previously described in the table "Functions Supported for Character,
Date and Value Expressions."
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LISTING THE DATABASE TO THE SCREEN
The LIST option on the DATA menu allows you to look at the information in
your database. The list produces an on-screen report that lists the data
one record at a time. If your database contains too many fields to be
displayed on the screen at one time, the list procedure will ask you at
which field to begin the display.
ZAP A DATABASE
The Zap option allows you to quickly erase all records from a
database. To use this option, open a database, then choose Zap.
KILL - DELETE A DATABASE
The Kill option allows you to delete a database and its related
missing values files (if any.) When you choose this option, a list of
databases will appear on the screen. Choose the database to delete,
and the file(s) will be erased from your disk.
QUIT/EXIT KWIKSTAT
Use this option to end the Kwikstat program and return to DOS.
PART IV
PERFORMING A STATISTICAL ANALYSIS
This section of the KWIKSTAT manual describes the statistical analysis
procedures available in the basic KWIKSTAT program.
USING DESCRIPTIVE STATISTICS AND GRAPHS
The Descriptive Statistics and Graphs module allows you to examine
summary statistics of the data in a database. Graphics are used
throughout KWIKSTAT to provide visual displays of the data.
DETAILED STATISTICS ON A SINGLE VARIABLE
This option calculates the mean, standard deviation, median, standard
error of the mean, minimum, maximum, sum, and variance of a set of
data. In this option, KWIKSTAT also calculates five percentiles and
computes a two-sided confidence interval about the mean. If you do not
specify otherwise, the default percentiles (Tukey's five number
summary: 0, 25th, 50th, 75th, 100th percentiles) and default level of
confidence (95%) are used. If the Tukey five number summary is used, a
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box plot is also displayed. For sample sizes less than or equal to 30,
a t-statistic is used to calculate for confidence interval. For sample
sizes over 30, the 95% (two-sided) z-statistic (1.96) is used.
SUMMARY STATISTICS ON A NUMBER OF VARIABLES
This option is similar to the above Descriptive statistics on a single
variable, but in this option several variables can be summarized using
descriptive statistics (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. You are also given the opportunity to
print results to the printer, or to output results to a file.
APPROXIMATE P-VALUE DETERMINATION
This option calculates p-values for entered values of four test
statistics: normal (z), student's t, F, chi-square. If you designate the
statistic being used, degrees of freedom and the calculated value of the
test statistic, KWIKSTAT will tell you the p-value associated with that
test statistic.
PRODUCING A HISTOGRAM
This procedure produces a histogram from values read from a database.
A histogram can be helpful in determining if the distribution of a
continuous variable is approximated by a normal distribution. If the
histogram has a peak toward the center, with both tails diminishing,
the data could be considered to be approximated by a normal
distribution.
PRODUCING AN XY-PLOT (SCATTERPLOT)
This option enables you to produce a scatterplot of two variables. A
scatterplot is simply a plot of all the data values plotted one variable
against the other. Such a plot is helpful in determining if two variables
are related, and if the relationship is linear (a straight line),
curvilinear, or something else. This information is important for
regression and correlation. (Scatterplots can also be produced from the
Regression & Correlation module.)
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EXAMPLE 4.5: SCATTERPLOT
This example uses the EXAMPLE database file on the KWIKSTAT disk.
Suppose you want to create and display a scatterplot of the TIME1
variable against TIME2. First, you must retrieve the database:
RETRIEVING THE DATABASE
In the lower left corner of the screen you can see the name of the
database currently in use. If it's the one you want, EXAMPLE in this
case, go on to Performing the Analysis. If another database is in use,
see Example 4.2 for detailed instructions on retrieving EXAMPLE.
PERFORMING THE ANALYSIS
From the Descriptive Statistics and Graphs menu, select XY-Plot
(Scatterplot). You will be prompted to enter two fields, or variables,
to use. Since you want to do a scatterplot of TIME1 against TIME2,
enter 3,4. You will then be prompted for specifications for the plot.
You may use the default settings (by simply pressing Enter at each
prompt) or you may set your own. (The default setting is no grid lines
and points not connected.) KWIKSTAT will draw the scatterplot
according to the specifications. The disappearing menu at the bottom
of the screen gives you the option to (P)rint. (Press Enter to make
the bottom menu reappear.) You can use the (R)eplot option to play
around with the specifications of the scatterplot. Pressing Esc takes
you back to the Choose Analysis Option menu.
Figure 4.4 shows the scatterplot of TIME1 and TIME2 of the EXAMPLE
database using default specifications. This plot suggests that the two
variables, TIME1 and TIME2 are related positively. As TIME1 increases,
so does TIME 2.
TIME SERIES PLOT
This option enables you to produce a time-series plot for one variable.
This plot is useful in examining data that is time related, such as
profit by month, etc. The X axis is assumed to be "time". The data
values must be entered into records in chronological order the
observations occurred, i.e., the first record must contain the results
of the first observation (first time period), etc.
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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. For example, if you do an experiment in
which you give different treatments to different groups (e.g., different
fertilizers to different groups of plants), the response measurements
(e.g., plant heights) will very likely all be different and the average
responses for the different groups will be different.
PARAMETRIC INDEPENDENT GROUP ANALYSIS
Independent group analysis is appropriate when observations are taken
from groups in which subjects in one group do not appear in another
group. That is, the observations within as well as between groups are
independent of one another. In this module, a t-test is performed when
there are two groups, and an ANOVA is performed when there are three to
ten groups being compared. When performing a t-test or ANOVA on two or
more independent groups, you are testing the hypotheses:
Ho: The difference in the means of the groups is zero.
Ha: The difference in the means of the groups is not zero.
For a two-sample t-test, two t-statistics are calculated, one for the
case in which the variances of the two samples are equal and the other
for use in the case of unequal variances. KWIKSTAT performs a test
of the hypothesis that the variances are equal. If the p-value is
small (e.g., less than 0.05), the hypothesis of equal variances is
rejected and you use the t-statistic for unequal variances. If the
p-value is large, use the t-statistic for equal variances. Since the
observations are all independent of one another, each observation is
entered as an individual record in the database. The number of data
records must be the same as the total number of observations. Each
record includes the response value of one observation and a number or
character to indicate to which treatment group it belongs. That is,
there will be two fields (variables), one in which to record the
response and one in which to indicate the group.
EXAMPLE 4.8. 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
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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
CREATING A DATABASE
The database to analyze this data is similar to the one used for
Example 4.7 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.
Create a database (named e.g., HOGFEED) with two fields: GROUP (or you
may want to call this field FEED) and WEIGHT. The groups will be
numbered 1,2,3,4 according to the type of feed used. The contents of a
database option, the HOGFEED database should look like this:
RECNO GROUP 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
PERFORMING THE ANALYSIS
Select the Analyze menu. When the Analyze pull-down menu appears,
choose the t-tests and Analysis of Variance (ANOVA) option. The
t-tests and Analysis of Variance Choose Analysis Option menu will
appear. Select Compare independent groups (t-test, ANOVA).
You will be prompted to choose the field name of the grouping variable,
which in this case is GROUP. Choose GROUP. Next, you will be asked for
the data field. Choose WEIGHT, the response variable. KWIKSTAT will
now perform the calculations and display the results on the screen, as
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illustrated in Figure 4.7.
The results of this test are summarized in the p-value. In this case,
the small p-value (0.000) means that there is a significant difference
between groups. The p-value (rounded off) is less than 0.0005. That
is, the difference between these observed averages is so far from zero
that the chance of getting differences farther from zero is less than
five in 10,000 if the true means are equal (their difference is zero).
This is taken as evidence of a "real" difference between feeds, a
difference not due to chance. A p-value of this magnitude is often
reported as p <.01 in research literature.
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, press M to choose (M)ultiple comparison. The Newman-Keuls
multiple comparison test will describe which of the means are
significantly different from which others (at the 0.05 significance
level).
Figure 4.8 displays a graphical representation of the Newman-Keuls
multiple comparisons test. 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 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.
Box plots are also available to graphically illustrate the differences
between the groups. Type G (for graphical comparison) and press Enter
to produce the plots.
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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. Repeated measures may
also be matched subjects.
In this module, as in the independent groups module, a t-test is
performed when there are two groups (two repeated measures), and an
analysis of variance is performed by KWIKSTAT if there are three to
ten groups. The ANOVA determines if there is a difference in the means
across groups or repeated measures. A multiple comparison procedure
further identifies where the differences lie.
In a database for paired or repeated measures data, each record
represents one subject (e.g., person, animal). There must be one field
for each repeated measure (each treatment group). For paired data,
there are two groups, hence two fields. Thus, in each record, there is
a field in which to enter data from each observation (treatment) on
that subject. This repeated measures (paired) analysis requires that
all values be available for each subject and any subject with missing
values is eliminated from the analysis. That is, a data record must
have a value for each field, or it will be eliminated.
The hypotheses being tested with a paired t-test or a repeated measures
ANOVA is:
Ho: There is no difference among means of the groups (repeated measures).
Ha: There is a difference among means of the groups.
For comparing matched or paired data (not independent) from two groups, a
paired t-test is used.
EXAMPLE 4.9: 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).
Data for paired t-test
Person Before After
1 162 168
2 170 136
3 184 147
4 164 159
5 172 143
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6 176 161
7 159 143
8 170 145
CREATING THE DATABASE
The database will include two fields (BEFORE and AFTER) and eight
records, one for each person. Since the observations are paired, not
independent, the database reflects this by having each record contain a
pair of observations. Each record, that is, each person, is independent
of the over seven persons, but within a record, the before and after
observations are not independent of each other. To create this database:
Create a database called DIET containing the data list above. Use
the pre-defined database structure called,
FOR PAIRED T-TEST OR McNEMAR's TEST
This will create a database with the fields VAR1 and VAR2. The VAR1 will
be used for Before and VAR2 will be used for After. Of course, you can
choose to create a custom database and enter a structure containing the
fields named BEFORE and AFTER.
Enter the data into the database. The data you will enter in the first
record is 162 (press Enter) and 168 (press Enter). Enter the data for
the eight records. When you exit the entry procedure, KWIKSTAT will
return to the Data main menu.
PERFORMING THE ANALYSIS
Select the Analyze option form the main KWIKSTAT menu. Next, choose
the t-tests and Analysis of Variance (ANOVA) option. The t-test and
Analysis of Variance Choose Analysis Option menu will appear. Then
choose Compare repeated or paired data (t-test, ANOVA).
You will be prompted to choose the fields which you wish to compare.
Choose BEFORE and AFTER. KWIKSTAT will now perform the calculations
and display the results on the screen.
The means and standard deviations for each group are displayed, but
more importantly, the mean difference between BEFORE and AFTER
measurements is given. The statistical procedures are performed on
this average difference. A 95% confidence interval for the mean
difference is given, as well as a calculated t-statistic and a
p-value. These results are interpreted like those of a single sample
t-test with null hypothesis: mean=0, and alternative hypothesis: mean
<> 0.
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The calculated t-statistic is 2.37. The test is performed with 7 degrees
of freedom, and the p-value associated with the test is 0.008. A small
p-value such as this is usually interpreted to indicate rejection of the
null hypothesis and leads to the conclusion that the average difference
in BEFORE and AFTER weights is not zero, i.e., there is evidence of a
significant (at the 0.05 level) change of weight in these eight subjects
on average. Since KWIKSTAT uses the difference "second minus first
variable" (i.e., "before minus after") to compute the t-statistic, and
since the mean difference is positive, on average before weights are
greater than after weights which implies that the change is loss of
weight on average.
INDEPENDENT GROUP TESTS FROM SUMMARY DATA
This option allows you to perform a one-way ANOVA or a t-test if you
have only the means, standard deviations and group sizes of two to ten
groups. Since data are summary, no box plots can be given.
USING NON-PARAMETRIC COMPARATIVE 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.
NON-PARAMETRIC INDEPENDENT GROUP ANALYSIS - MANN-WHITNEY AND
KRUSKAL-WALLIS TESTS
This option is appropriate if you are comparing two or more
independent groups, but you cannot make the assumption that the
observed data follow a normal distribution or that the variances are
equal. It is also useful if you do not have exact data values for the
observations but you do have order statistics, that is, you don't know
the exact response values but you know which is largest, next largest,
and so forth, to smallest. The samples must be randomly and
independently taken from populations that differ only with respect to
location, and the variable of interest should be continuous. See Zar,
1984.
In the Non-Parametric Comparison Tests Module, KWIKSTAT uses the
Mann-Whitney procedure if two independent groups are being compared,
and the Kruskal-Wallis procedure if three or more groups are being
compared. The hypotheses being tested are:
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Ho: There is no difference in the medians of the groups.
Ha: There is a difference in the medians of the groups.
The Mann-Whitney and Kruskal-Wallis non-parametric procedures differ from
the independent groups analysis described in the previous section in that
the ranks, or order, of the data are used for the analysis rather than
the data values themselves.
FRIEDMAN'S TEST
When repeated observations are taken from the same subject, and there
is interet in comparing the observations for each repeated measure
(e.g., each type of treatment), then a repeated measures analysis may
be appropriate. If you cannot make the assumption that the data are
normal, the a nonparametric analysis is appropriate. One method of
performing such as test the Friedman's Analysis.
COCHRAN'S Q TEST
Cochran's Q test is a non-parametric procedure appropriate for use
with dichotomous data when the experiment involves repeated measures
on blocks. Often the blocks are subjects (people or animals). 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 measurment.
USING REGRESSION & CORRELATION PROCEDURES
To examine the linear relationship between variables, correlation and
linear regression are used.
Simple linear regression is used for predicting a value of a dependent
variable using an independent variable. Multiple regression is used
for predicting the value of a dependent using one or more independent
variables. Correlation is used to measure the strength of association
between two variables. For example, you may be interested in relating
advertising to orders received. The question you are asking is, "Is
there a relationship between the amount of money spent on advertising
and the amount of orders received?" It is also possible to compare
more than two variables at a time using multiple regression. For
example, you may be interested in how the combination of radio
advertising costs, direct mail costs and commissions relate to the
number of orders received.
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SIMPLE LINEAR REGRESSION ANALYSIS
When you choose the Simple Linear Regression option, KWIKSTAT will
prompt you to choose the "independent" and "dependent" variables to be
used in the analysis. The "independent" variable is generally that
variable that you can choose, regulate or specify (e.g., amount of
money spent on advertising) and the "dependent" variable is the one
you observe and would possibly like to predict. After the two
variables are chosen, KWIKSTAT will present the results of its
calculations.
The regression equation will be displayed along with other results.
This equation is the "least squares" line fitted to the data. If the
fit is appropriate, the equation may be used to predict a new value of
the dependent variable given the value of the independent variable,
within the range of the original data.
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.
Refer to a good text on the subject before making any conclusions
about your results.
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).Also displayed is R-square (R2), as well as adjusted
R-square. R-square varies from 0.0 to 1.0, with 0.0 meaning no
relationship (model is not good) and 1.0 meaning the regression
equation perfectly describes the sample data.
An analysis of variance is performed to determine the overall
significance of the model. If the ANOVA reveals a significant
relationship, (that is, if the p-value is small) the model may be a
good representation of the sample data.
A plot of residuals from the fit is available. You may plot the fit
against any of the variables. Look for patterns in the residuals.
Patterns other than a horizontal band about zero suggest that the
assumptions necessary for regression analysis may be violated. If you
are unfamiliar with multiple regression, the Neter and Wasserman book
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contains an excellent treatment.
EXAMPLE 4.20: 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.
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). Figure 4.15 displays the LONGLEY database. You can get
this display by using the List (display) the contents of a database
option on the Data main menu.
PERFORMING THE ANALYSIS
Open the LONGELY database. From the Analyze menu in the main KWIKSTAT
module, select the Regression & Correlation module. From the
Correlation and Regression menu select Multiple Linear Regression
analysis. You will be prompted to enter the INDEPENDENT VARIABLE(S),
which in this case are DEFLATOR, GNP, UNEMP, ARMED, POP, TIME. Enter
any combination of 1,2,3,4,5,6 to choose the variable(s) you wish to
analyze against TOTAL. One way to approach a multiple regression
problem is to first include all of the independent variables. After
initial analysis (see below) you may decide to eliminate those
independent variables found to not be significant.
After entering the independent variables, you will be asked for the
DEPENDENT VARIABLE. Enter 7, which chooses TOTAL. KWIKSTAT will now
perform the calculations and display the results on the screen, as
illustrated in Figure 4.16.
EXAMPLE 4.22: CORRELATION MATRIX (LONGLEY DATA)
Select the Correlation matrix option from the Regression and
Correlation menu. You will be prompted to choose variables from the
list of fields that appears. In this case, there are seven fields, and
you can choose any combination of them. If you want correlation
coefficients of all pairs of the seven variables, type 1,2,3,4,5,6,7
and press Enter. KWIKSTAT will perform the calculations and display
the 7 by 7 array shown in Figure 4.17. 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
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array consists of two numbers (three numbers if the information is
viewed or 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. If you view the resuts,
the third (bottom) number, in brackets, is the sample size, or number
of paired observations used in the calculations.
Both the correlation coefficient and the p-value are interpreted as they
are for any correlation of two variables (see Example 4.21 above). In
this array, for example, POP and TIME are highly correlated (r=0.994,
p=0.00) but POP and ARMED are not (r= 0.364, p=0.17).
EXAMPLE 4.23: GRAPHICAL CORRELATION MATRIX (LONGLEY DATA)
From the Simple and Multiple Regression Choose Analysis Option menu,
select Graphical Correlation matrix. You will be prompted to choose
variables from the list of fields that appears. In this case, there
are seven fields, and you can choose any combination of them. If you
want correlation coefficients of all pairs of the seven variables,
type 1,2,3,4,5,6,7 and press Enter. KWIKSTAT will perform the
calculations and display the 7 by 7 array of scatterplots shown in
Figure 4.18.
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. The more highly correlated two variables
are, the more tightly clustered about a straight line are the points
on the scatterplot.
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. Previous examples using measurement data include
weights of hogs, weights of people, heights of plants, numbers of
handguns and homicides, and dollar amounts. If, rather than taking a
measurement, a data observation involves identifying which of a set of
categories the observation falls into, you are working with
categorical data.
For example, you may identify a person by sex, eye color or hair
color. You may identify families, individuals or institutions by
geographical region or socioeconomic status identified by levels
1,2,3,4,5. You may identify employees by level of job satisfaction,
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where there are three or four levels to choose from.
Generally, categorical data are entered into a database by using one
record for each person or entity on which the observation is made and
one field for each characteristic which is divided into categories.
For example, to categorize ten people by sex, hair color and eye
color, you would need ten records (one per person) and three fields
(e.g., SEX, HAIR, EYE). Some of the procedures in this module give you
the choice of simply entering totals for each category rather than
creating a database and entering the results of each observation. This
can save time if totals are known and only totals are needed to
perform a test or calculation or to produce a graph.
PERFORMING A FREQUENCIES ANALYSIS
In the Frequencies option, KWIKSTAT "counts" the occurrence of each
data value for a single variable or field and displays that
information in a table. You can also create a bar chart, pictograph
and/or pie chart of this information using this option.
EXAMPLE 4.24: FREQUENCY TABLE, PICTOGRAPH, BAR AND PIE CHARTS
This example uses the EXAMPLE database file on the KWIKSTAT disk. 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. Open the EXAMPLE database.
Performing the Analysis
From the Frequencies and Crosstabulations Choose Analysis Option menu,
select Frequencies, Pictograph, Pie Chart. You will be prompted to
enter one field (variable) to use. Since you want to do a frequency
table on STATUS, enter 7. KWIKSTAT will count the data in each of the
five categories of STATUS and display the results as a frequency
table.
You are then prompted to press Enter, which takes you to the Frequencies
Analysis menu. From this menu you may choose to go back and do another
analysis, or create charts.
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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. The data observations must be independent
and each data value can be counted in one and only one category. It is
also assumed that the number of observations is fixed. The hypotheses
being tested are
Ho: The population distribution begin samples follows the hypothesized
distribution.
Ha: The population does not follow the hypothesized distribution.
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. It
must be possible to assume that the data observations are independent
and that each data value can be counted in one and only one category.
It is also assumed that the number of observations is fixed. KWIKSTAT
allows you to enter data for a two-way table from the keyboard or from
a database. When you choose to enter the two-way table from the
keyboard, KWIKSTAT will ask you the size of the table (number of rows
and columns). A blank table will be presented on the screen, and you
will then be prompted to enter a number in each cell of the table.
If you choose to enter the information from a database, KWIKSTAT will
prompt you to enter a list of tables to be calculated. For example '2 BY
3' specifies a tablulation of field 2 by field 3. The specification '1
BY 2,3' specifies the tables 1 BY 2 and 1 BY 3. You may list up to ten
field numbers on both sides of the BY. KWIKSTAT will read the information
from the database, and construct the table or tables. For instance, in
the EXAMPLE database, if you choose to tabulate the variables GROUP and
STATUS, KWIKSTAT will form the table on the screen as illustrated in
Figure 4.23. (Note that the first variable entered is the row
variable.)
When requesting multiple plots in the BY specification, you will be
given the option to choose to pause after each table is displayed, or
to continue non-stop and print all of the requested tables to the
printer to to a file.
For a test for independence, a contingency table looks at two
categorical variables from a single sample of one population and tests
whether the two variables are related in some way, (e.g., are sex and
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hair color related?)
The hypotheses being tested are:
Ho: The variables are independent of each other. (There is no
association between them).
Ha: The variables are not independent of each other.
KWIKSTAT reports both the chi-square statistic and the p-value. If the
expected value (Eij) in one or more cells is less than 5, the
chi-square test may not be valid. A warning to this effect appears on
the screen if appropriate. In the case of a 2 by 2 table, Fisher's
Exact Test and the chi-square with Yates' correction are also
performed and results displayed.
EXAMPLE 4.26: CROSSTABULATION ANALYSIS (2 BY 2) 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.
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. A decision can be made
using the p-value of the test. A low p-value (less than or equal to
the chosen significance level) is usually taken to indicate rejection
of the null hypothesis. At a 0.05 significance level, the Fisher's
Exact Test p-value of 0.050 indicates (on the borderline) that there
is enough evidence to reject the null hypothesis of independence of
the two variables and to conclude that leaf side and type of insect
are not independent. In this case it appears that beetles prefer the
upper sides of leaves and bugs are about split in their preference. In
the case of the Yates results, this decision is marginal. After
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viewing the crosstabulation results, press Enter and a
Crosstabulations Analysis menu will appear. This menu gives you the
options of doing another analysis, printing what you have done, or
producing a 3-dimensional bar chart. Select by highlighting the
desired option and pressing Enter.
DRAWING A 3-D BAR CHART
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 of the Frequencies and Crosstabulations Choose
Analysis Option menu. To get to this menu from the Data main menu,
select Analyze at the top of the screen, and then select
Crosstabulations, Frequencies, Chi Square.
MCNEMAR'S TEST
McNemar's test is appropriate for use with paried, dichotomous data.
This test is sometimes called a test for related samples or a test for
the significance of changes. It is used ehen the response is one of
only two possible outcomes. McNemar';s test is the 2 by 2 version of
Cochran's Q test described earlier. The test assumes that any pair of
observations is independent of any other pair or observations,
although clearly the observations with a pair are not independent of
each other.
USING LIFE TABLES AND SURVIVAL ANALYSIS PROCEDURES
As the name indicates, this module performs life tables and survival
analysis procedures. 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.
Once the data are entered into the program, a life table for each
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group is produced which includes, for each time interval, the number
entered, withdrawn, lost, dead, exposed, the proportion dead,
proportion surviving, cumulative proportion surviving, hazard and
density. 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 test is performed to test the hypothesis of equal
survival patterns for the groups.
A small version of the survival plot will appear on the screen, and if
you choose to print a report of the session the report will include a
larger version of the plot along with other information from the
analysis.
PERFORMING A LIFE TABLE ANALYSIS
Survival analysis is used to summarize information in life tables, to
examine survival trends over time, and to compare survival times
between groups.
EXAMPLE 4.31A: LIFE TABLE ANALYSIS
The data for this example are in the LIFE database on the KWIKSTAT
disk. These data are from Prentice (1973).
Open the database named LIFE. The LIFE database consists of 3 fields:
SURVIVAL, CENSOR, and GROUP. Figure 4.30 displays a portion of the
LIFE database. You can get this display by using the List (display)
the contents of a database option on the Data main menu.
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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APPENDIX
INTERPRETING ERROR CODES
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. Many times, you can correct this
error situation by understanding what caused it. For example, if you
were to get an error number 27, you would know that it was caused by
your printer sending an "Out of Paper" message to the program. If you
are unable to resolve the problem, write down the steps taken before
the error occured, and send it to TexaSoft on the Problem Report Form.
We will try to resolve the problem as quickly as possible.
Error Codes:
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 print out of the results or Print Screen.
KWIKSTAT VERSION YOU ARE USING:________________________
KWIKSTAT MODULE where problem occurred:____________________
YOUR COMPUTER: BRAND/Model_____________________________
MONITOR TYPE:________AMOUNT OF MEMORY:_______________
VERSION OF DOS YOU ARE USING:____________________________
MEMORY RESIDENT PROGRAMS YOU USE:____________________
PROBLEM:
Mail to:TexaSoft, P.O. Box 1169, Cedar Hill, Texas 75104. Or fax to
214-291-3400, or send E-Mail to Compuserve 70721,3145.
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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
---- -----------------------------------------------------
____ More "BY GROUP" capabilities
____ Ability to sort database
____ Add more ANOVA types
____ Add more Non-parametric statistical tests
____ Add General Linear Model
____ Make Report more flexible
____ Add Quality Control Module
____ Speed up program functions
____ Add more graphics, what kind?
____ Improve graphic quality
____ Add cluster analysis
____ Add discriminant analysis
____ Automate analysis from a command file
____ _____________________________________________
____ _____________________________________________
Other Comments:
Mail to:TexaSoft, P.O. Box 1169, Cedar Hill, Texas 75104. Or fax to
214-291-3400, or send E-Mail to Compuserve 70721,3145.
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S H A R E W A R E
_________________
TRY IT BEFORE YOU BUY IT
The purpose of shareware products is to allow you to try software
products before you buy them. KWIKSTAT is not a public domain
program. Persons who use KWIKSTAT on a regular basis should purchase a
copy. You receive several benefits from becoming an official
registered user:
1. You help to keep the product growing to meet your needs.
2. You receive the very latest version, with a printed, bound, and
expanded manual.
3. You receive periodic newsletters announcing new releases, and
pointing out important information on any bugs and fixes.
4. You are able to purchase update to new versions for a minimal cost.
Print the file on disk named KSORDER.TXT to register. Thanks.
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└────╨────┘ MEMBER
This program is produced by a member of the Association of Shareware
Professionals (ASP). ASP wants to make sure that the shareware
principle works for you. If you are unable to resolve a shareware-
related problem with an ASP member by contacting the member directly,
ASP may be able to help. The ASP Ombudsman can help you resolve a
dispute or problem with an ASP member, but does not provide technical
support for members' products. Please write to the ASP Ombudsman at
545 Grover Road, Muskegon, MI 49442 or send a CompuServe message via
CompuServe Mail to ASP Ombudsman 70007,3536.
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