Contents

Introduction

Statistics

Customizing

Handing Variables

Menu commands

Hotkeys

Registration

What do you get with registered version


Windows

From windows menu you may activate one of the windows openened in Statistics.

The default is Output where you can see your output data. As you execute Graphics commands windows are created by Statistics to view your graphics, these windows titlles are appended in Windows menu item so you may view them at any time you desire by selecting this menu item from the Windows menu.


Customizing general
General

Make cpecific  configuration for you spreadsheet.

 Row, Columns. Specify the number of rows, columns for you spreadsheet.

There is not need to specify big values for this fields.

Less values you can use will make your package faster and will free memmory for your system.

The default values for is 600 rows(Observs), 40 columns (Variables). You may change these fields at any  time of your work.

 Missing Values. Specify the value of missing values for you spreadsheet.

Missing values are ignored when Statistics are running statistics on your spreadsheet.

Default missing values for Statistics package is also the space and comma characters.

Missing values are very important for the computes on each variable.

 Formatted output. Click this checkbox if you want to change the output format of data cells. You may specify the thousands,decimals  separator character, the maximum output length of numbers and the number of decimals.

Note: The thousands,decimals  separator is based on your windows environment configuration.

Usualy you will never need to change these fields.

 Autoload last file. Check this checkbox if you want Statistics to load the last work sheet every time you run it.

General

Messages

 Wrong data typing. Customize Statistics of witch action to take when invalid data entered from users.

You may require statistics to display a fatal error message,

convert wrong data to missing values or ignore the error.

Note: If you check hold value as is you may have unpredictable results with statistics.


Customizing

Colors

Fonts,Justifications

General


Tools

The [tools] toolbar allow you to customize the apperance of your data.

You may change the  font,fontsize,style,Color,text justification of your data.

Note:

if the following toolbar is not visible on your spreadsheet  then Click on Config|Tools menu item.


Colors

With this option you can customize your spreadsheet colors.

You may change foregound,background colors for the actual data cells and data titles.

The FG, BG status on colors panel specifies the selected  forground (FG), background (BG) color for the speradsheet

Cells color may changed by  clicking on Data RadioButton and titles colors by clicking on Titles  RadioButton .

You may view changes by click on button  View  and undo changes with button Undo.

Color confirmation for spreadsheet becomes valid only after clicking button OK


Menu commands

File

Edit

Statistics Variables

Graphics

Windows

Config


Speed Buttons


Sort

Sort observs of variable defined in the "Sort by"  edit box.

In the "Variables follow" list box you may enter any variable name that you want to be sorted depending on the "Sort by"

Select sort order by clicking in one of the check boxes for order.


Select cases

Select or exclude rows in statistics computes.

Enter a mathimatical formula in boolean evaluation to select or exclude rows for statistics computes or even delete rows from the spreadsheet wich the don't satisfies the boolean mathematical formula

Click on Delete excluded rows check box if you want the rows to be deleted. Warning: if you delete rows from the spreadsheet there is no way to recover.

Example: Suppose that we have the following data in out spreadsheet

and that we want to select all rows with var2 equals 1 then we type in the formula window the following

The spreadsheet will now look like this.

The rows marked with an X will not take place to any computationals.

Attention: Variable names are case sensitive.


Compute

From this dialog you may recalculate cell values using mathimatical formulas.

In the formual you may even make computes based on other cell values.

Example:

: Var1 = abs(:Var1)+:Var2-sqr(:Var2)

This fourmula will compute a new value for its cell of var1 based on the values of var1,var2 variables cells.

You may create a new variable if you just click on then " Create variable" check box.

Register version will come with more functions.

Attention: Variable names are case sensitive.


Recode

Change cell  values of selected variable.

Define ranges of values in the "From", "To" columns and change the actual value of every observation  in variable to the "Value" column if the cell has a value in range "From"  to  "To"


Introduction

Demo  version .

This statistical  package  contains  basic  statistical  tests  useful  to  those  who  have  an  interest  in  statistics. We included some basic  tests  and we hope to provide users with  a good and cheap solution.

If  you  are  interested  in  this  software  please  see Registration

This software has been developed by :

George Katsabouris :Statistician. Nick Ameladiotis :Programmer.

If   you  have any questions, comments or suggestions please

contact  us  via  e-mail  to amela@telecom.ece.ntua.gr.

If you discover any bugs or problems please contact the developers at the above e-mail address,

specifing the problem and giving exact actions that led you  to the bug  or problem.

Also specify the date the bug encountered. We  will   fix the bug and  let you know the site you can  retreive the fixed version.

We  Thank  you  and we hope that  you will  find this package useful as we did.


Statistics

Descriptives

Frequencies

Mean Values

t-test

Inference from proportions

Analysis of variance

Correlation

Regression


Descriptives

The following statistics are displayed: size of sample, number of missing observations, mean,

median, minimum, maximum, range, sum, standard deviation, standard error of mean,

variance, coefficient of variation, moment coefficients of skewness and kurtosis, mode and

standard  errors  of  kurtosis  and  skewness.


Frequencies

The   following  information  is  displayed: the  number  of  cases  for  each  category  of  the

selected  variable, the percentage  of  values  and  missing  values  and  the  sum  of  all

the  above.


PG6
Registration

Nick Ameladiotis

Skyrou 76,  113 62

Athens

Greece

REGISTRATION FORM STATISTICS ============================

Name: ...........................................

Company Name: ..........................................

Address: ...........................................

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Phone Number: ...........................................

E-Mail Address: ...........................................

Nr. of copies: .............

Additional comments, suggestions, complaints,  etc:

............................................................

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Registration fee is $80.

Send this order form along with  your  payment  to the address above

If   you  have any questions, comments or suggestions please contact  us at the above address or via  e-mail  to amela@telecom.ece.ntua.gr.

If you discover any bugs or problems please contact the developers at the above e-mail address.


Mean Values

The following statistics are displayed: mean, standard  deviation  and  standard  error  for

each   category  of  the  variables  selected.


One Sample T-Test

The null hypothesis that the population mean is equal to the given mean is tested. Population

variance is assumed to be unknown.

One or more columns may be selected by clicking on [Variable]. The test will be performed

for each column independently. After variable selection the program prompts for the given

mean. Missing values are omitted by case. Output includes the basic statistics, computed t

value, degrees of freedom, the two-tailed significance level and the confidence interval for

the specified confidence level.


Two Sample T-Test

The data for this test can be in one of the two  types supported for two sample tests

By  using  the  first  option  you  have to  select  a  variable  that  contains  all

the  cases  needed  for  the test  and  a  factor  variable  which  divides  the  data

variable  into  discrete  categories.

By  using  the  second  option each  column  contains  data  and  the  test performs

for  pairs  of  columns.

Missing values are omitted by case and the degrees of freedom is adjusted accordingly.


Paired Sample T-Test

A paired t-test is performed between two variables, such as values of a sample before and

after a certain treatment. The null hypothesis tested is that the difference between pairs is

zero against the alternative hypothesis that the difference between pairs is not equal to zero.

Two or more columns can be selected by clicking on [Variable]. The test will be

performed between all possible pairs, as long as they have equal number of observations.

For each test, any pair of cases with one or more missing values is omitted and the degrees

of freedom is adjusted for missing values.

Output contains basic statistics on data and the test results.


Crosstabs

The  crosstabs  procedure  produces  bivariate  tables  and  two  very  common  test  statistics,

the chi-square statistic  and  the  likelihood-ratio  statistic.

This  procedure  is  very  commonly  used  in  social  science  research  at  all  levels.

The procedure will sort each column separately, determine the number of categories in each

column and then count the frequency of occurrence of every combination of categories. For

instance, in a two-way analysis, if the variable in the first column takes on values 0, 1, and 2

and the variable in the second column takes on four different values such as 3, 4, 5 and 6,

the program will produce a 3 by 4 table (number of rows by number of columns).


Spearman Correlation

Correlation between relative rankings of the two variables is measured rather than their

nominal values. In this way each variable is transformed into a uniformly distributed variable

and the effect of outliers is minimised.

Pairs with at least one missing value are omitted and the degrees of freedom is adjusted.

Output includes the correlation coefficient, t statistic, degrees of freedom and the one or  the

two  tailed significance levels.


Pearson Correlation

The Pearson correlation coefficient  is  a  useful  tool  for  quantifying the  relationship

between  pairs of  variables.

The  correlation coefficient  has  played  an  important  role  in  the  history  of  statistical methods.

It  is  now  of  considerably  less value  than  the  regression  coefficients. If  two  variables  are

correlated  it  is  usually  much  more  useful  to  study  the  positions  of  one  or  both  of  the

regression  lines, which  permit  the  prediction  of  one  variable in  terms  of  the  other, than  to

summarize  the  degree  of  correlation  in  a  single  index.

Pairs with one or more missing values are omitted and the degrees of freedom is adjusted.

Output includes the correlation coefficient, t-statistic, degrees of freedom and the one or  the

two  tailed significance levels.


Partial Correlation

The  technique  of  partial  correlation  can  be  used  when  a  researcher  wishes to  observe  how

a  specific  bivariate  relationship  behaves  in  the  presence  of   several  other  variables.

By  observing  the  partial  correlation  coefficients, spurious and  intervening relationships

can  be  detected, and  the  causal  relationships  among  the  variables can be probed.

The program will consider each pair of variables separately, and calculate coefficients for

only those pairs with equal number of cases. Also, the program will handle missing values for

each pair of columns separately and omit pairs of cases with at least one missing value.


Mann Whitney u-test

The Mann whitney u-test  has  many  similarities  with  the  test  of  significance  for  the  difference

in  sample  means. In  both  cases  we  compare random  samples  as  a  way  of  making

inferences about  the  possible  differences  between  two  populations. In  both  cases, the  test

statistics  are  computed  from  the  samples  and  compared  with  the  sampling  distribution  of  all

possible  outcomes. Instead  of  computing  means  as  the  sample  statistic, however, the  Mann Whitney test

is  based  on  the  ranking  of  the  sample  scores. This  is  an  appropriate  basis, since  ranking  is

the  most  sophisticated mathematical  operation  that  can  be  performed on ordinal-level  data.

Output includes number of cases, rank sums, mean ranks, and U scores for the two samples

as well as the test statistic,the  correction for ties and the two tailed significance level.


Wilcoxon rank sum test

This test is designed  for  the  sitution  where the  two  samples  are  not  independent,

that  is, when  the  samples  have  been  matched  on  some  criterion  as  in  a  ''before-after''

test  of  the  same  subjects.

The two samples are assumed to consist of matched pairs. Absolute values of the difference

between the pairs are ranked and the rank sums of negative and positive differences are computed.

Two or more columns can be selected from the variable list by clicking [Variable]. The test

will be performed on all possible pairs with equal Missing values are omitted pairwise.

Output includes the number of positive and negative differences, rank sums and mean ranks

as well as the test statistic, Z value and its two tailed significance level.


Sign  test

Negative and positive differences are counted and the ties are ignored. Since the probability

that either sum exceeds the other is .5 the test becomes equivalent to a binomial test with p

= .5.

If N < 25 then the exact probability is calculated from the binomial distribution. Otherwise

significance level is based on a normal approximation:

Two or more columns can be selected from the variable list by clicking [Variable]. The test

will be performed on all possible pairs with equal length. Missing values are omitted

pairwise. The output consists of the number of negative and positive differences, number of

ties, the test statistic and its two-tailed probability.


McNemar test

This test determines the difference in proportions of two dichotomous variables. The chi-

square statistic with one degree of freedom is compared with the chi-square distribution.

Output includes the table, the chi-suare statistic  and  the  significance  level.


Kruskal - Wallis one-way anova

A  generalization  of  the  Mann Whitney test  to  more  than  two  groups  is  given by  the

Kruskal- Wallis one-way  analysis  of  variance. This  test  is  based  on  ranking all  the  values

and  then  the  test  proceeds  by  a  method  which  has  similarities  with  a  one-way analysis

of  variance  on  the  ranks.

Columns selected for this test need not be of equal lengths and the missing values are

omitted by case. Output includes the rank sum and mean rank for each variable

and the correction for ties. The one tail probability is reported using  the chi-square

distribution .


Friedman two-way anova

This test is a  generalization of  the  sign  test  to  more  than  two  groups.

Cases are ranked and the mean rank is calculated for each sample.

Chi-square statistic is used. Output includes the rank sum and mean rank for each variable

and the correction for ties. The one tail probability is reported using  the chi-square

distribution .


Multiple regression

The general purpose of multiple regression is to learn more about the relationship between

several independent or predictor variables and a dependent or criterion variable.

Polynomial, exponential, logarithmic  and  inverse  models  are  provided  by  the  package.

Pairs with at least one missing value are omitted and the degrees of freedom is adjusted.

Output includes the correlation coefficients and their standard  errors, t statistic, degrees of freedom  and the significance levels. In  addition, it  includes  an  analysis  of  variance  table  with  its  F - statistic and  the

significance  level.


One-way Anova

This  test  is  ageneralization  of  the  two  sample t-test  for  more  than  two variables.

The null hypothesis that  three  or  more   population means are equal is tested. It is assumed

that the several   populations are independent and their standard deviations are the same.

Missing values are omitted by case and the degrees of freedom is adjusted accordingly.


Keys
Hotkeys

You may use the following keys when entering data

Ctrl-Insert                 Insert an empty row

Ctrl-RShift-Insert       Insert an empty column  (Variable)

Ctrl-Delete                Delete focused row

Ctrl-RShift-Delete     Delete focused column

Ctrl-M                       Enter missing value into focused cell

Ctrl-Home                 Move focus to top-left cell

Home                       Move at the first column of the current row

End                          Move at the last column of the current row

Ctrl-PgUp                 Move focus to top of active view

Ctrl-PgDn                 Move focus to bottom of active view

F10                          Activates menu


Selecting variables
Select variables

Selecting variables for running statistics is some how the same for all of the dialogs in the package

The basic view of dialogs is the one follows. In  the variables listbox you may see all the variables that may be used in statistics computes.

The select variables list box containts the actual variable(s) witch will take place in the final computes.

With the  Variable button you may select or deselect variables for the final computes.

To move one variable to the Select Variables listbox you may select the desired variables

and then click on the Variable button. Or even simplier you can just double click on the variable name you want set select. Depending on witch listbox has the focus accordinaly the variable button arrow changes showing the transfer (from witch listbox to we move variable names) witch will take access after clicking on it.


Variables
Handling Variables

Selecting variables in dialog boxes

Define variable Recode

Compute

Select cases


Define variable

What can you do if you don't want do see just number on our spreadsheet ?

Here is the solution. You just go into define variables dialogs.

In the label column you enter the text (only ?)  that you want Statistics to display for the desired value entered in the value column.

That means that if a cell has the value 1 and we want to see "Male" we enter "Male" in the label column and "1" in Value column.

 Use New name if you want to change the variable name

 Use Clear button to clear Labels, Values for the variable

 Use Undo button to undo any changes

Note:

You may specify up to 512 different values and lables.


PG27
File

 New          Create new data file

 Open         Open existing Data,Text,ODBC data

Data is the actual Statistics file in witch Statistics saves your work

Text is ant free text file witch may contain valid observrs for Statistics

ODBC not available in Unregistrer

 Save         Save data file

 Save as..  Save data file with new name entered from user

 Exit.          Just exit program


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Edit

  Cut. Cut data from spreadsheet and copy to clipboard

  Copy. Copy data to clipboard

  Paste. Paste data from clipboard

  Repeat

  Find. Find a cell value

  Replace. Replace a cell value

  Sort

  Insert. Insert rows, columns in spreadsheet


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Variables


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Graphics


PG51
Repeat

Repeat the specified "Value" entered, n "Times" . You may repeat values across rows or columns by simple clicking the one of the rows, columns Check boxes.


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find


t-test

One Sample T-Test

Two Sample T-Test

Paired Sample T-Test


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inference from proportions


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analysis of variance

One-way Anova


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correlation

Pearson correlation

Partial correlatgion

Spearman correlation


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Regression

Multiple regression


Non parametric tests

Sign test

Wilcoxon rank sum test McNemar  test

Friedman two-way Anova

Kruskal - Wallis one-way anova

Mann - Whitney u-test


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What do you get with registered version

  Full custom support (Upgrades, Bug reports, New versions)

  More graphics

  More functions for uses with Compute, Select cases options

  ODBC ( Open Database Connectivity) with you may retreive data from any known database like Paradox, Access, Oracle, Sybase, Interbase, DB2 and more

  Load free text values for your spreadsheet from any document

  More powerfull help with examples and Readers references

  Support on statistics tests via  E-Mail for how you can make your tests have successfull results

  Unlimmited rows,columns in your spreadsheet

  and at last you may save and restore your spreadsheet

See how to Register know


E-Mail

If   you  have any questions, comments,suggestions or bug reports please

contact  us  via  e-mail  to amela@telecom.ece.ntua.gr.