InnerSoft STATS - Application Manual v1.7

7/27/2019 InnerSoft STATS - Application Manual v1.7

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InnerSoft STATS

Application Manual v1.7

http://isstats.itspanish.org/
http://isstats.itspanish.org/http://isstats.itspanish.org/http://isstats.itspanish.org/


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APPLICATION MANUAL V1.7 InnerSoft STATS

INDEX

1.

Installation and Activation

1.1.Installation

1.2.Trial Version

1.3.

Activation1.4.License

1.4.1. Upgrades

1.4.2. License Renewal

2. Introduction to ISSTATS

2.1.Open and Save files

2.2.Technical Limitations and Recommendations

3. Working in the Main window

3.1.File Menu

3.2.

Analyze Menu3.3.Graphs Menu

3.4.Help Menu

4. Working in the Project Manager window

4.1.Root

4.2.Settings

4.3.Variables

5. Working in the Worksheet window

5.1.File Menu

5.2.Edit Menu

5.3.

Options Menu

5.4.View Labels

6. Working in the Output window

7. Frequency Tables

8. Descriptive Statistics

9. Crosstabs

10.One Sample Test

10.1. Z Test

10.2. T Test

10.3.

Variance Test11.Two-Sample Test

11.1. 2-Sample t-Test

11.2. Paired t-Test

11.3.

2 Variances F-Test

12.

One-Way ANOVA

13.

Homoscedasticity Tests

14.

Bivariate Correlation Tests

15.

Parametric Value at Risk

16.

Exponentially Weighted Moving Average (EWMA) Forecast17.

Financial Formulas

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1. Installation and Activation

1.1. Installation

Click on setup.exe to install the application.

1.2. Trial Version

InnerSoft STATS works initially as limited trial version. You will not be allowed to use the following

tools:

Open or Save any Project or Worksheet.

Using Paste or Insert when editing cells.

1.3. Activation

In order to use InnerSoft STATS Full Version, user must purchase a license before activating the product.To purchase InnerSoft STATS Full Version, you must first contact with us by email

[email protected]

[email protected]

You can also call us (Spain number phone):

There are different payment methods that you can find at:


Once product has been paid, you can activate it. Just enterHelp/Activate ISSTATS and follow instructions.

For a successful activation process, InnerSoft requires permissions to read/write files in its installation

folder, usually: 'C:\Program Files\ISSTATS\'.

So may you have to login to Windows asAdministratoror have to modify User Account Controlin order

to activate successfully InnerSoft STATS.

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1.4. License

Registering data is chained to a PC Computer. When you pay a license, you can run InnerSoft STATS in

3 different computers. Thus you can ask for 3 Activation Codes.

You will not lose the license when formatting the hard drives or changing Windows S.O., BUT if you

make changes of hardware the activation code may become invalid.

Extra Activation Codes (more than 3) for same user have an additional cost.

1.4.1. Upgrades

You will receive the Activation Codes for the product upgrades at no cost during one year. If you do not

renew the license after one year, will not lose the license of the product version that you purchased, BUT

will not receive new Activation Codes for the new software versions.

1.4.2. License Renewal

The renewal will let you receive the Activation Codes for the new versions of the software during a year.

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2. Introduction to ISSTATS

When you start ISSTATS, a new, empty project is opened for you. You will see three windows:

Main window

o

Project Manager windowo Worksheet window

o Output window

Controlling Windows

You can open and minimize ISSTATS windows just as you would other windows in your operating

system. You can also control ISSTATS windows with commands on the Window menu.

ISSTATS Environment

The project contains:

A Worksheet that contains your data. You can NOT have multiple worksheets in one project. Your data

will be displayed as columns. There is a Data window for your worksheet in the project. You can enter

and edit data directly in the Data window.

A Project Manager, which contains:

A Root folder for setting the project information.

A Settings folder for setting some options.

A Variables folder for your worksheet. This folder displays a summary of the columns used in theworksheet.

An Output window that displays your results.

Multiple Toolbars for issuing commands and a Status Bar.

2.1. Open and Save files

Use the file menu to open, close or save the three file types that ISSTATS can use.

Projectscontain a worksheet, along with project settings and project information

Worksheetscontain only your columns data

Outputscontain the computed outputs

When you open a project file, the worksheet that were inside that project when you last saved is available

to you. When you save a project, the worksheet is saved within that project file.

The output results must be saved apart from the project file.

ISSTATS does not support multiple Worksheets or multiple Output documents. If you create a new table

or document, remember to save the previous data before it disappears.

You can save a project or worksheet in XML or Binary file format. The advantages and disadvantages of

using each format are:

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XML

XML format is human readable and editable in plain text

Can be imported by lot of applications (Excel)

Takes high size: storing a variable with 15 millions of values will take around 50 Mb in a XML

file

Has a high compression rate: a XML file of 50 Mb will get only 1 Mb of size once compressed inzip format

Opening and saving is fast

Binary

Binary format is not human readable

Can be only open by ISSTATS

Takes less size than XML: storing a variable with 15 millions of values will take around 30 Mb

in a Binary file.

Has a low compression rate: a Binary file of 50 Mb will get 6 Mb of size once compressed in zipformat.

Opening and saving is slow.

Thus XML compressed in zip is the better way of storing large amounts of data.

2.2. Technical Limitations and Recommendations

ISSTATS uses decimal data type instead of double data type. Decimal is specially used for financial and

monetary calculation which requires higher accuracy. It is not adequate for scientific applications because

of its lower range: the largest value is +/7.9228162514264337593543950335, and the smallest nonzero

value is +/0.0000000000000000000000000001 (+/1E28). Thus if you need to analyses social or

scientific data with large numbers (astronomy distances, human stupidity), just use a different statistical

package.

ISSTATS work with onmemory data (no database storage). Thus it can compute quickly. In the other

hand, memory usage is huge.

ISSTATS can handle millions of data. It can compute all descriptive parameters of a variable with 15

million values in only a few seconds (Processor: Pentium R Dual Core CPU E 6600 @ 3.06 GHz 3.07

GHz RAM: 8.0 GB SO: Windows 7 64 Bits). In the other hand, the Data table can easily crash if you tryto manipulate this huge data. Operations like copying, pasting, removing and selecting cells in such a big

table can hang the application. It really depends on the total number of cells in the table. To avoid this

problem, limit the number of table columns when operating with huge data. If you want to handle

variables with millions of values, set the number of table columns to minimum in the Worksheet

OPTIONS menu: if you are using only 4 variables, set only 4 columns.

You should perform operations with columns as much as possible. If you want to clear a variable, select

the column and clear the column; avoid selecting all cells in the column and clearing these cells. If you

want to copy a variable then copy the column, not the cells.

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Actually, undo/redo history has no limits. A limit will be implemented in a future. If you feel that

ISSTATS is consuming too much memory in your PC, you should save your project, restart the

application and open your project again. This will clear the undo/redo history.

Please, remember this is an early version.

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3. Working in the Main window

3.1. File Menu

New Project

Creating a new project closes the current project. If your current project has been changed since it waslast saved, ISSTATS will prompt you to save all or part of the project before closing it.

Open Project

Opening a new project closes the current project. If your current project has been changed since it was

last saved, ISSTATS will prompt you to save all or part of the project before closing it.

Save Project

Saves the current project in a XML or Binary file. If the project has been saved before, Save Project

saves the file with the current file name without displaying a dialog box. If the project has not been saved

before, Save Projectopens the Save Project Asdialog box.

When you save the project, you save the input information about your work:

the contents of project settings and project information

the columns of data in the Worksheet window

The output document will not be saved in your project file.

Save Project As

Saves the current project in a XML or Binary file with a different name. If the project has not been saved

before, choosing File > Save Projectalso opens this dialog box.

Dialog box items

Save in: Choose a drive and folder.

File name: Enter a file name.

Save as type: Choose afile type from the list.

o XML files (*.xml)

o

DAT files (*.dat)

Exit

Exit you from ISSTATS. ISSTATS will prompt you to save the changes before closing the application.

3.2. Analyze Menu

Frequency Tables: SeeChapter 7. Frequency Tables

Descriptive Statistics: SeeChapter 8. Descriptive Statistics

Crosstabs: SeeChapter 9. Crosstabs

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One Sample Test: SeeChapter 10. One Sample Test

Two-Sample Test: SeeChapter 11. Two-Sample Test

One-Way ANOVA: SeeChapter 12. One-Way ANOVA

Homoscedasticity Tests: SeeChapter 13. Homoscedasticity Tests

Bivariate Correlation Tests: SeeChapter 14. Bivariate Correlation Tests

Parametric VaR: SeeChapter 15. Parametric Value at Risk

EWMA Forecast: SeeChapter 16. Exponentially Weighted Moving Average (EWMA) Forecast

Financial Formulas: SeeChapter 17. Financial Formulas

3.3. Graphs Menu

General Settings

Most of the menus have a tab for general settings. The options are:

Chart Width. Determines the width of the entire chart image in pixels.

Chart Height. Determines the height of the entire chart image in pixels.

Opacity. To use an opaque color, set Opacity to 255. To create a semitransparent color, set

Opacity to any value from 1 through 254 (0=Total Transparency; 255=Total Opacity). You must

set some grade of transparency when using multi-series charts based on superposed areas: Radar,

Range, Area, SplineRange, SplineArea

Border Width for Lines. Determines the border width, in pixels, of the chart. Use if for line-based

charts as Candlestick, FastLine, Line, PointAndFigure, Spline, StepLine, Stock,

ThreeLineBreak

Use 3D Style. Check to display the chart area using 3D style.

Is Right Angle Axes.Gets or sets a flag that determines whether a chart area is displayed using an

isometric projection. Check to display the chart axes at right angles. Uncheck to display the chart

area using an isometric projection.

Y Axis is Started From Zero. Indicates whether the minimum value of the axis will be

automatically set to zero if all data point values are positive. If there are negative data point

values, the minimum value of the data points will be used.Check if the minimum value of the axis

is automatically set to zero when all data point values are positive.

Y Axis Scale Break Style. A scale break is a stripe drawn across the plotting area of a chart to

denote a break in continuity between the high and low values on a value axis. Use a scale break to

display two distinct ranges in the same chart area.You cannot specify where to place a scale break

on your chart. The chart uses its own calculations based on the values in your dataset to determine

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whether there is sufficient separation between data ranges to draw a scale break on the value axis

(y-axis).

Label Y Values. Check to display the data point value as labels.

Show Legend. Check to display the chart legend.

There is also a common tab to set the Title and Footnote of the chart. Click Titles Tab to define lines of

text to be placed at the top or bottom of the plot. None of these fields is required. You may choose to

leave any or all of them blank.

Group of Cases

From the menus choose: Graphs > Group of Cases

Available type charts are

Area

Bar

Bubble Column

Doughnut

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FastLine

FastPoint

Funnel

Line

Pie

Point

Pyramid

Radar

Spline

SplineArea

StackedBar

StackedBar100

StackedColumn

StackedColumn100

Available statistics are

Number of cases

% of cases

Cumulative N

Cumulative %

You can arrange groups in ascending or descending order of the categories values. You can also arrange

groups in ascending or descending order of the group values.

Display missing as a group. This option is available only when you use a categorical variable to define

groups for a new chart. If selected, each system-missing value for the grouping variable will appear as a

separate group in the chart. If not, cases with system-missing or user-missing values for the grouping

variable are excluded from the chart.

Categorical-Quantitative

From the menus choose: Graphs > Categorical-Quantitative

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Mean of values Median of values

Mode of values

Number of values

Sum of values

Standard deviation

Variance

Minimum value

Maximum value

Cumulative sum


Area

Bar

Bubble

Column

Doughnut FastLine

FastPoint

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Funnel

Line

Pie

Point

Pyramid

Radar

Spline

SplineArea

StackedBar

StackedBar100. Not available for Cumulative %.

StackedColumn

StackedColumn100. Not available for Cumulative %.

StepLine

You can arrange groups in ascending or descending order of the factor variable values. You can also

arrange groups in ascending or descending order of the dependent variable values.





Two Categorical

From the menus choose: Graphs > Two Categorical

1.

Select at least one variable for the category axis and move it into the Independent Variable (x)

field. This variable may be numeric or string.

2.

Select at least one variable and move it into the Dependent Variable (Y) field. Each group will

consist of one bar/slice/stack/lines for each value of the Dependent variable at every level of the

Independent variable.

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Number of cases. % Grand Total. Percentages are based on the total number of cases or responses in the chart.

% by X.Percentages are based on the total number of cases in the x-axis category. Adding up the

graphic elements in the category equals 100%.

% by Y.Percentages are based on the total number of cases in the y-axis category. Adding up the

graphic elements in the category equals 100%.

Cumulative N. The cumulative number of cases with particular x-axis values. Each graphic

element shows the number of cases with particular x-axis values plus the total number of cases for

every graphic element drawn previously on the same axis.

Cumulative %.The cumulative percentage of cases with particular x-axis values. Each graphicelement shows the percentage of cases with particular x-axis values plus the total percentage of

cases for every graphic element drawn previously on the same axis.


Area. Set some grade of transparency to see all different series.

Bar

Bubble Candlestick

Column

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FastLine

FastPoint

Line

Point

Radar. Set some grade of transparency to see all different series.

Spline

SplineArea. Set some grade of transparency to see all different series.

StackedArea.

StackedArea100. Not available for statistics % by Y and Cumulative %.

StackedBar.

StackedBar100. Not available for statistics % by Y and Cumulative %.

StackedColumn.

StackedColumn100. Not available for statistics % by Y and Cumulative %.

StepLine.





Graph Sequences

From the menus choose: Graphs > Sequences

1. Select at least one variable for the y- axis and move it into the Sequence Variable (Y) field. This

variable must be numeric.

2. Optionally, you can select a variable as Label X Variable. This variable may be numeric or string.

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Checking One chart per variable, each variable produces a chart. Checking One Sequence per

variable, all variables are drawn in a unique chart; each variable produces a series or sequence.


Area

Bar

Column

FastLine

FastPoint

Kagi Line

Point

Radar

Renko

Spline

SplineArea

StepLine

ThreeLineBreak

The Kagi/Renko/ThreeLineBreaktab contains some settings for these charts.

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For Kagichart, the options are

Reversal Amount: Specifies the reversal amount for the chart. When used with the Kagi

chart, this custom property defines when a new Kagi line should be drawn.This value may

be a percentage or fixed amount.For example: 1.2 or 4%.

For Renkochart, the options are

Box Size: Specifies the box size of the Renko chart, as either a percentage or a fixed value.

For ThreeLineBreakchart, the options are

Number of Lines in Break: Specifies the number of lines to use in a Three Line Break

chart.

Candlestick/Point and Figure/Stock Graph

From the menus choose: Graphs > Candlestick/Point and Figure

Available type charts are:

Candlestick. Require High, Low, Open and Close variables.

PointAndFigure. Requires High and Low variables.

Range. Requires High and Low variables. If Open and Close variables are also defined, it will

draw two different range series: High-Low series, and Open-Close series.

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2.

You can select a variable and move it into the Set Markers By field. Each value of this variable is

marked by a different symbol on the scatterplot. This variable may be numeric or string.

3.

You can select a numeric or a string variable and move it into the Label Cases By field. You can

label points on the plot with this variable.

a.

If selected, the value labels (or values if no labels are defined) of this variable are used as

point labels.

b.

If you do not select a variable to label cases by, other options can be used to label points.i.

No Label

ii. Case Number

iii. Coordinates

iv. Y value

3.4. Help Menu

Contents

Open this PDF.

Buy ISSTATS

Open a web page with information about buying InnerSoft STATS.

Activate ISSTATS

Open the menu to activate ISSTATS in order to use all features.

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About

Shows ISSTATS version and contact information.

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4. Working in the Project Manager window

4.1. Root

The root menu shows the following properties of the project:

Default folder Owner

Description

You can access some other menus using the tree at the left.

4.2. Settings

Set the Output Decimal Places in this menu. The default value is 3.

4.3. Variables

This menu shows the following properties of each variable:

Name

Column Id

Count

Missing

Typeo Numeric

o Text

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Scale of measure

o Nominal

o Ordinal

o Scale

o Unknown

Description

Values

Clicking in the Values button, you can access the Value Labels menu.

You can assign descriptive value labels for each value of a variable. This process is particularly useful ifyour data file uses numeric codes to represent non-numeric categories (for example, codes of 1 and 2 for

Man and Woman). Value labels are saved with the data file. You do not need to redefine value labels each

time you open a data file.

To specify value labels of a variable:

1. For each value, enter the value and a label.

2.

Click Add to enter the value label.3. Click OK

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Then, displays a windowfrom which the user can specify some importing options.

Choose the Excel Worksheet you want ISSTAS to open from WorkSheet to Importdrop-down list.

Check the columns of the selected worksheet that you want to import from Columns to Importcheck box

list. The first cell value of each column is shown to help you identify them.

ClickRead variable names from the first row of dataif the first row of the spreadsheet contains columnheadings.

Choose the Import Mode

Import Mode Mixed: ISSTATS determines the datatype of an Excel column by examining the

actual values in the first 10 rows and then chooses a datatype that represents the majority of the

values in its sampling. If most of these cells are numeric, the variable will be imported as numeric

and any text or empty cell will be considered a missing value. If most of these cells are texts, the

variable will be imported as nominal-text and any empty cell will be considered a missing value.

Import Mode Strict: At first, a variable is supposed to be numeric. Empty cells are supposed to be

missing values of a numeric variable. If ISSTATS detect any text in the Excel column, then the

variable will be imported as text-nominal. Column headings are excluded from this rule if Read

variable names from the first row of datais checked.

ISSTATS will read the Excel worksheet as a rectangular array of data. If the Excel columns havedifferent number of cells, ISSTATS will display some variables with some missing values at the bottom.

In order to use this command, some users may have to install 2007 Office System Driver: Data

Connectivity Components at

http://www.microsoft.com/en-us/download/details.aspx?id=23734

Export to Excel

This tool export to Excel only those columns that has a variable defined. Empty columns will not be

exported.

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Exporting to Excel has some limitations. As worksheet limit size in Excel 2010 is 65,536 rows, ISSTATS

will divide the data collection in different sheets of 65530 rows everyone. If you are going to export 15

million values, the application will create 23 different Excel worksheets with 65530 rows each one. As

columns limit in Excel 2010 is 256 columns, ISSTATS will not export the data of more than 256

variables.

5.2. Edit Menu

Undo & Redo

To undo an action, click Undo Button on the Toolbar.

To redo an action that you undid, click Redo Button on the Toolbar.

Cut Cells

The selection will be copied to the clipboard buffer. The selection will be moved to a new location as

soon as you choose Paste command as described below.

Please note that the selection will remain in its current location until you paste it. If you want to delete a

selection without pasting it to a new location, use Delete command instead.

Copy Cells

The selection will be copied to the clipboard buffer. The selection will be copied to a new location as

soon as you choose Paste command as described below.

You can copy all the cells of a column or a row selecting the rows or columns and using the COPY

CELLS button. To avoid copying the variable names, when you select some columns and click the COPYCELLS button, the name cells of the column is deselected.

Paste Cells

The contents of the clipboard will be pasted in the spreadsheet so that the selected cell becomes the top

left corner of the selection.

When you paste cells, the blank cells that you cut/copied will not modify any existing value and will not

add any new value to the column. The missing values that you copied will add new missing values or will

replace the existing ones with missing values.

If you copy a discontinuous group of cells, by selecting cells or block of cells while holding down the Ctrl

key, ISSTATS will paste it as a continuous selection where non selected cells are converted in empty

strings.

Insert Cells

You can insert copied cells above of the active cell on your worksheet, shifting other cells in the same

column down.

After you insert cells, the blank cells that you previously copied will add missing values. Inserting cellsbelow the last value of the column will do as pasting cells: blank cells will not add data.

Clear Cells

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Erases the contents of the selected cells, without moving other cells. This menu command is available

when at least one cell is selected in the Data window. To delete selected cells, see Delete Cells.

In a numeric column, ISSTATS inserts system missing values (*) in a cleared cell.

Delete Cells

If you are deleting cells, other cells automatically shift up.If you click a cell and then press DELETE,ISSTATS deletes the cell contents.

Select All Cells

Click this button to select all cells on the worksheet.

Copy Columns

When you copy various columns, alternated selected columns will be joined together in a continuous

selection once you paste or insert them (as Excel does).

Paste Columns

On pasting, empty selected columns will not modify any existing variables. Not empty selected columns

will replace any existing variables.

Insert Columns

You can insert columns that previously copied in the worksheet.

To insert a single column, select the column in the column immediately to the right of where you want to

insert the new column. To insert multiple columns, select the columns immediately to the right of whereyou want to insert columns.

If you insert columns, other columns automatically shift to the right.

On inserting, empty columns (no variable defined) will add new empty columns (no variable defined).

Clear Columns Content

Erases the contents of the selected column, without moving other columns. This menu command is

available when at least one column is selected in the Data window. To delete selected columns, see Delete

Columns.

The cleared cells remain as blank cells on the worksheet.

Delete Columns

If you are deleting columns, other columns automatically shift to the left.

Select All Columns

The Select All Columns command will create a new selection that includes every column with data.

As rows have not any structural meaning in the table, there is no copy/cut/paste/insert options for rows. If

you want to copy all cells of a row just select the rows and press COPY CELLS button.

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5.3. Options Menu

Table Decimal Places

For numbers that are already entered on a worksheet, you can increase or decrease the number of places

that are displayed after the decimal point by using the Table Decimal Places buttons. By default,

ISSTATS displays 3 decimal places when you apply a built-in number format to the cells.

Table Columns

You can increase or decrease the number of columns that are available in the worksheet by using the

Table Columns buttons. By default, ISSTATS displays 10 columns.

To avoid memory problems, limit the number of table columns when operating with huge data. If you

want to handle variables with millions of values, set the number of table columns to minimum: if you are

using only 4 variables, set only 4 columns.

Table Rows

You can increase or decrease the number of rows that are available in the worksheet by using the Table

Rows buttons. By default, ISSTATS displays 100 rows.

5.4. View Labels

If variables contain value labels, you can control the display of variable labels and data values clicking on

button View Labels.

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6. Working in the Output window

New Document

Creating a new output document closes the current document. If your current document has been changed

since it was last saved, ISSTATS will prompt you to save the document before closing it.

Open Document

Opening a new document closes the current document. If your current document has been changed since

it was last saved, ISSTATS will prompt you to save the document before closing it.

The file format of the opened document must be ISSTAT XAML package (a XAML package file

produced by ISSTAT).

Save Document

Saves the current document in a ISSTAT XAML package file (a XAML package file produced by

ISSTAT). If the document has been saved before, Save Documentsaves the file with the current file

name without displaying a dialog box. If the document has not been saved before, Save Documentopens

the Save Document Asdialog box.

Use Windows Clipboard to copy and paste the document content in other applications, such as MS Word,

MS Excel, Notepad

Save Document As

Saves the document in a file. Use this command if you want to rename your document or save it to a new

location.

Print Document

Prints the document.

Cut, Copy & Paste

The way to copy or move a selection is to use cut, copy, and paste operations.

Use this commands to copy a selection from Output window to other applications, such as MS Word, MSExcel, Notepad

Undo & Redo

To undo an action, click Undo Button on the Toolbar.

To redo an action that you undid, click Redo Button on the Toolbar.

Bold, Italic, Underline, Grow Font, Shrink Font, Bullets, Numbering, Align Left, Align Center,

Align Right, Align Justify, Increase Indent & Decrease Indent

These are the formatting buttons, familiar to anyone who has used a word processor. These formats are

applied by selecting some text in the window and clicking the button in the editor toolbar.

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Select All

The Select All command will create a new selection that includes everything on the document.

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7. Frequency Tables

Overview

The frequency of a particular observation is the number of times the observation occurs in the data. The

distribution of a variable is the pattern of frequencies of the observation.

Frequency distribution tables can be used for both categorical and numeric variables. Use numeric codes

or strings to code categorical variables (nominal or ordinal level measurements).

Dialog box items

Order by. The frequency table can be arranged according to the actual values in the data or according to

the count (frequency of occurrence) of those values, and the table can be arranged in either ascending or

descending order.

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8. Descriptive Statistics

Overview

Produces descriptive statistics for each column. The data columns must be numeric and contain at least

one numeric value. The dialog box allows to choose the statistics that you wish to display.

Available Variableslist shows numeric data columns containing at least one no-missing value.

Dialog box items

Mean: Choose to display the arithmetic mean.

Sample Variance: Choose to display the unbiased variance of the data. Estimates population variance

based on a sample. If your data represents the entire population, then compute the variance by using Total

Variance.

Sample Standard Deviation: Choose to display the standard deviation of the data.Estimates populationstandard deviation based on a sample.If your data represents the entire population, then compute the Std.

Deviation by using Total Std. Deviation.

Sample Coefficient of variation: Choose to display the coefficient of variation.

Sample Skewness: Choose to display the skewness value.Estimates population skewness based on a

sample.If your data represents the entire population, then compute the skewness by using Total

Skewness.

Sample Kurtosis: Choose to display the kurtosis value.Estimates population kurtosis based on a sample.

If your data represents the entire population, then compute the kurtosis by using Total Kurtosis.

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Total Variance: Choose to display the variance of the data. Calculates variance based on the entire

population.

Total Standard deviation: Choose to display the standard deviation of the data.Calculates Std. Deviation

based on the entire population.

Total Coefficient of variation: Choose to display the coefficient of variation. Calculates coefficient of

variation based on the entire population.

Total Skewness: Choose to display the skewness value.Calculates skewness based on the entire

population.

Total Kurtosis: Choose to display the kurtosis value.Calculates kurtosis based on the entire population.

SEM: Choose to display the standard error of the mean.

Sum: Choose to display the data sum.

Minimum: Choose to display the data minimum.

Maximum: Choose to display the data maximum.

Range: Choose to display the data range.Data Range is the difference between the maximum and

minimum.

Quartiles: Choose to display the first quartile, the median and the third quartile.

Interquartile range: Choose to display the difference between the first and third quartiles.

Deciles: Choose to display the nine values that divide the sorted data into ten equal parts.

Percentiles: To request a percentile:

Enter the desired value in the box placed in Percentiles group box. For example, if you wanted the

7thpercentile, you would enter a 7 in the box.

Click the add button to add the percentile to the list of requested percentiles.

Repeat Step 1 and 2 to add additional percentiles as desired.

If you need to delete a percentile, select it in the list and click the remove button.

Mode: Choose to display the mode and the number of times it occurs. If multiple modes exist, Minitab

displays the smallest modes, up to a total of four, along with their frequency.

Sum of squares: Choose to display the sum of the squared data values. This is the uncorrected sums of

squares, without first subtracting the mean.

MSSD: Choose to display half the Mean of Successive Squared Differences.

N nonmissing: Choose to display the number of nonmissing column entries.

N missing: Choose to display the number of missing column entries.

N total: Choose to display the total (nonmissing and missing) number of column entries.

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CutPoints: Divide the data into a number of equal groups. For example, to create deciles, you would

enter 10 in the box .Enter 3 to divide the data into tertiles.

Check statistics

Check None: Choose to clear all check boxes and then individually check the statistics to display.

Check All: Choose to check all boxes. You can uncheck statistics as needed.

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9. Crosstabs

Dialog box items

Available Variableslist shows numeric data columns containing at least one no-missing value. Enter at

least one variable in the Rows box. Enter at least one variable in the Columns box.

Cells Dialog box

Check the content of the table cells.

Statistics Dialog box

Check the test to perform.

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The Chi-Square box includes:

Pearson Chi-Square Test

Yates's Continuity Correction (only for 2-by-2 square tables)

Likelihood Ratio G-Test

Mantel-Haenszel Chi-Square Test

For further details, see Methods and Formulas Help: Pearson Chi Square Test.

The Fishers Exact Test box includes:

One sided and two sided Fishers Exact Test (only for 2-by-2 square tables)

For further details, see Methods and Formulas Help: Fishers Exact Test.

The McNemar box includes:

If the table is a 2-by-2 square matrix

McNemar asymptotic

Edwards Continuity Correction

McNemar Exact Binomial

Mid-P McNemar Test

If the table is a k-by-k square matrix, with k > 2

McNemar-Bowker Test

For further details, see Methods and Formulas Help: McNemars Test.

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The Risk box includes:

Odds Ratio

Relative Risk

Attributable risk

Relative Attributable Risk

Number Needed to Harm

Attributable Risk per Unit

Etiologic Fraction

Risk Estimate statistics are only computed for a 2-by-2 square table without empty cells

For further details, see Methods and Formulas Help: Risk Test.

The Kappa box includes:

Cohen's Kappa Test (only for k-by-k square tables)

For further details, see Methods and Formulas Help: Cohen's Kappa Test.

The Contingency Phi Cramer box includes:

Phi Coefficient

Contingency Coefficient

Standardized Contingency Coefficient

Cramer's V

Tschuprow's T

The Lambda box includes:

Symmetric Lambda

Asymmetric Lambda (Row variable as dependent)

Asymmetric Lambda (Column variable as dependent)

The Goodman and Kruskal tau box includes:

Asymmetric Uncertainty Coefficient (Row variable as dependent)

Asymmetric Uncertainty Coefficient (Column variable as dependent)

The Uncertainty Coefficient box includes:

Symmetric Uncertainty Coefficient

Asymmetric Uncertainty Coefficient (Row variable as dependent) Asymmetric Uncertainty Coefficient (Column variable as dependent)

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The Ordinal box includes:

Gamma

Sommers d

Kendalls tau-b

Kendalls tau-c

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Dialog box items

Data: Choose the origin of the data.

Samples in columns:Choose if you have entered raw data in columns. Enter the columns

containing the sample data in the list Computing Variables. Move these variables from Available

Variables list to Computing Variables list using Add and Remove buttons. Enter the value for the

population standard deviation in the text box. Entering multiple columns, ISSTATS performsseparate one-sample analyses on each column.

Summarized data: Choose if you have summary values for the sample size and mean.

o Sample size:Enter the value for thesample size.

o Mean:Enter the value for the sample mean.

o Population Standard deviation:Enter the value for the population standard deviation.

Confidence level: Enter the level of confidence desired. Enter any number between 0 and 1. Entering 0,9will result in a 90% confidence interval. The default is 0,95 = 95%.

Perform hypothesis test:Check to perform the hypothesis test.

Hypothesized mean:Enter the test mean 0.

Alternative hypothesis: Choose the alternative hypothesis of the test.

10.2. T Test

Performs aone-sample t-test or t-confidence interval for the mean.

Use T Test for one sample to compute aconfidence interval and perform ahypothesis test of themean

when thepopulation standard deviation, , is unknown. Use this test when samples come from a normal

population or n > 30.

Dialog box items


Samples in columns:Choose if you have entered raw data in columns. Enter the columns

containing the sample data in the list Computing Variables. Move these variables from Available

Variables list to Computing Variables list using Add and Remove buttons. Entering multiple

columns, ISSTATS performs separate one-sample analyses on each column

Summarized data: Choose if you have summary values for the sample size and mean.

o Sample size:Enter the value for thesample size.

o Mean:Enter the value for the sample mean.

o

Sample Standard deviation:Enter the value for the sample standard deviation.

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Confidence level: Enter the level of confidence desired. Enter any number between 0 and 1. Entering 0,9

will result in a 90% confidence interval. The default is 0,95 = 95%.


Hypothesized mean:Enter the test mean 0.


10.3. Variance Test

This procedure calculatesconfidence intervals for thevariance of a population, and performs ahypothesis

test to determine whether the population variance equals a specified value. Use this test when samples

come from a normal population.

Dialog box items


Samples in columns:Choose if you have entered raw data in columns. Enter the columnscontaining the sample data in the list Computing Variables. Move these variables from Available

Variables list to Computing Variables list using Add and Remove buttons. Entering multiple

columns, ISSTATS performs separate one-sample analyses on each column.

Summarized data: Choose if you have summary values for the sample size and variance.

o

Sample size:Enter the value for thesample size.

o Sample Variance:Enter the value for the sample variance.




Hypothesized variance:Enter the test variance 20.


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11. Two-Sample Test

In the box Test Type, choose the test to perform:

2-Sample t-Test Paired t-Test

2 Variances F-Test

Hypothesis Test

To perform a hypothesis test, check the box Perform Hypothesis Testand choose the Alternative

Hypothesisof the test:

Less than: Perform a level test of H0: dagainst the one-sided alternative H1: < d

Not Equal: Perform a level test of H0: = dagainst the two-sided alternative H1: d Greater than: Perform a level test of H0: dagainst the one-sided alternative H1: > d

Significance level of the test () derive from the 1-value set in the Confidence Level text box.

If you choose a lower-tailedhypothesis test,an upper confidence bound will be constructed. If youchoose an upper-tailedhypothesis test,a lower confidence bound will be constructed.

Available Variableslist shows numerical and text columns containing at least one no-missing value.

Text columns may be used as Subscripts.

11.1. 2 Sample t-Test

Performs an independent 2-sample t-test and generates aconfidence interval.

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When you havedependent samples,use 10.2. Paired t-Test.

Use 2-Sample t-Test to perform ahypothesis test and compute a confidence interval of the difference

between two populationmeans when the populationstandard deviations,'s, are unknown.

Dialog box items


Samples in one column: Choose if the sample data are in a single column, differentiated bysubscript values (group codes) in a second column.

o Computing Variables: Enter the columns containing the sample data in the list

Computing Variables. Move these variables from Available Variables list to Computing

Variables list using Add / Remove buttons.

o Grouping Variable: Enter the column containing the sample subscripts to define the

groups. It may be a numerical or text column.

o Group 1/Group 2: Enter thesubscripts that define both groups.

o

Automatic Grouping: Check to let the application define automatically both groups. Itwill identify the first two different subscripts in the grouping variable.

Samples in different columns: Choose if the data of the two samples are in separate columns.

o First Sample: Enter the column containing one sample from Available Variables list.

o Second Sample: Enter the column containing the other sample from Available Variables

list.

Summarized data: Choose if you have summary values for thesample size,mean, and variancefor each sample.

o First Sample

Sample size 1: Enter the sample size for the first sample.

Mean 1: Enter the value for the mean of the first sample.

Sample Variance 1: Enter the value for the variance of the first sample.

o Second Sample

Sample size 2: Enter the sample size for the second sample.

Mean 2: Enter the value for the mean of the second sample.

Sample Variance 2: Enter the value for the variance of the second sample.

Assume Population equal variances: Check to assume that the populations have equalvariances.




Hypothesized mean:Enter the hypothesized difference between the two population means 1-2.


A difference of 0 suggests in the null hypothesis the equality between mean populations; H0: 1-2 = 0

against an alternative H1: 1-2 0

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A difference equal or less than 0 suggest in the null hypothesis that the first mean is equal or less than the

second; H0: 1-2 0 against an alternative H1: 1-2 > 0

A difference equal or greater than 0 suggest in the null hypothesis that the first mean is equal or greater

than the second; H0: 1-2 0 against an alternative H1: 1-2 < 0

Optionally, test ratios other than 0 (equality) can be specified. A difference of 2 suggests in the null

hypothesis the first mean is the second mean plus 2.

11.2. Paired t-Test

Performs apaired t-test.This is appropriate for testing the mean difference between paired observations

when the paired differences follow a normal distribution.

Use the Paired t command to compute aconfidence interval and perform ahypothesis test of the mean

difference between paired observations in the population. A paired t-test matches responses that aredependent or related in a pairwise manner. A typical example of the repeated measures t-test would be

where subjects are tested prior to a treatment, say for high blood pressure, and the same subjects are

tested again after treatment with a blood-pressure lowering medication. Paired samples t-tests are often

referred to as "dependent samples t-tests". When the samples are drawnindependently from two

populations, use11.1. 2 Sample t-Test.

Dialog box items


Sample in columns: Choose if you have entered raw data in two columns.o First sample: Enter the column containing the first sample from Available Variables list.

o Second sample: Enter the column containing the second sample from Available Variables

list.

Pairs must have two numerical values. Pairs that have a missing data in any of the

members are ignored.

Summarized data: Choose if you have summary values for thesample size,mean, and variance

of the difference.

o

Sample size: Enter the value for the sample size.o Mean of Differences: Enter the value for the mean of differences .

o Variance of Differences: Enter the value for the variance of differences s2d.




Hypothesized mean:Enter the hypothesized population mean of the paired differences d.


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11.3. 2 Variances F-Test

The2 Variances F-Test procedureperformshypothesis tests and computesconfidence intervals for the

ratios between two populations'variances.Use this test to determine if one treatment condition has more

variability than the other. Each population must follow the normal distribution.

Dialog box items


Samples in one column: Choose if you have entered data into a single column with a second

column ofsubscripts that identify the samples.

o Computing Variables: Enter the columns containing the sample data in the list

Computing Variables. Move these variables from Available Variables list to Computing

Variables list using Add and Remove buttons. Entering multiple columns, ISSTATS

performs separate analyses on each column.

o Grouping Variable: Enter the column containing the sample subscripts to define the

groups. It may be a numerical or text column.o Group 1/Group 2: Enter thesubscripts that define both groups.

o Automatic Grouping: Check to let the application define automatically both groups. It

will identify the first two different subscripts in the grouping variable.

Samples in different columns: Choose if you have entered the data for the two samples into

separate columns.

o First Sample: Enter the column that contains the data for the first sample from Available

Variables list.o Second Sample: Enter the column that contains the data for the second sample from

Available Variables list.

Summarized data: Choose if you have summary values for the sample sizes and variances.

o First Sample

Sample size 1: Enter the sample size for the first sample.

Sample Variance 1: Enter the variance for the first sample.

o Second Sample

Sample size 2: Enter the sample size for the second sample. Sample Variance 2: Enter the variance for the second sample.




Hypothesized ratio:Enter the hypothesized ratio between two populations variances 21/22.


A ratio of 1 suggests in the null hypothesis the equality between variance populations; H0: 21/

22 = 1

against an alternative H1: 2

1/22 1.

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A ratio equal or less than 1 suggest in the null hypothesis that the first variance is equal or less than the

second; H0: 21/

22 1 against an alternative H1:

21/

22 > 1.

A ratio equal or greater than 1 suggest in the null hypothesis that the first variance is equal or greater than

the second; H0: 21/

22 1 against an alternative H1:

21/

22 < 1.

Optionally, test ratios other than 1 (equality) can be specified. A ratio of 2 suggests the first variance is

double the second variance.

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12. One-Way ANOVA

Performs a one-wayanalysis of variance.You can also perform multiple comparisons. The response

variable must be numeric. The factor level column (grouping variable) may be numeric or text.

Dialog box items


Groups in different Columns

o Computing Variables: Enter the columns containing theresponse.Each column must

contain the data for one of the groups.

Groups in 1 Column

o Computing Variables: Enter the column or columns containing theresponse.ISSTATS

performs a ANOVA test for each of these columns.

o Grouping Variable: Enter the column containing thefactor levels.

Confidence level: Enter the confidence level.

For further details, see Methods and Formulas Help: ANOVA Test.

Multiple Comparisons: Use to generate grouping information tables and confidence intervals for the

differences between means, by different methods. Check to obtain confidence intervals for all pairwise

differences between level means using any of these methods.

Scheffe

Tukey HSD: Tukey's Honestly Significant Difference test.

Sidak

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13. Homoscedasticity Tests

These tests are used to test if k samples are from populations with equal variances. The response variable

has to be numeric. The factor level column (grouping variable) may be numeric or text.

Dialog box items


Levene's Test

BrownForsythe Test for equality of variances

Bartlett's Test

For further details, see Methods and Formulas Help: Homoscedasticity Tests.

Remark: ISSTATS does not cancel a test if any of the groups does not fulfill the conditions. It simply

rejects the group. To take part into a Levene or BrownForsythe test, a group must have at least one

element. To take part into a Bartlett's Test, a group must have at least two elements; moreover, the group

must have a non-zero variance. Thus, ISSTATS may use 4 of the groups to perform Levene's Test but

only 2 of the groups to perform a Bartlett's Test. It depends on the number of elements of each group.

You should read the Descriptive Statistics information to check the Rejected Groups and also should read

the Total Groups info of each test to check the number of groups being used in that test.

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14. Bivariate Correlation Tests

Dialog box items


Covariance. Computes the matrix of covariances.

Pearson. Computes the Matrix of the Pearson Product-Moment Correlation Coefficients.

Tau-b Kendall. Computes the Matrix of Kendall's Tau-b Correlation Coefficients.

Spearman. Computes the Matrix of Spearmans Correlation Coefficients.

Outputs

Outputs include:

Coefficient. It may be the Pearson, Spearman or Tau-b Kendall coefficient.

p-value (Bi.). A two-tailed significance level (bilateral test).

Significant. YES if the test is statistically significant(p-value = 1 Confidence Level).

N. Number of cases or paired observations (Xi, Yi) in the sample.

For further details, see Methods and Formulas Help: Bivariate Correlation Tests.

Remark: All tests use pairwise deletion mode, thus the statistical procedure uses cases that contain some

missing data. A case may contain 3 variables: VAR1, VAR2, and VAR3. A case may have a missing

value for VAR1, but this does not prevent some statistical procedures from using the same case to analyze

variables VAR2 and VAR3. Pairwise deletion allows you to use more of your data. However, each

computed statistic may be based on a different subset of cases.

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15. Parametric Value at Risk

Compute the Parametric Value at Risk by the Variance-Covariance Method.

Inputs

Choose the columns for daily return rates of each asset in a portfolio. Each of these columns must have a

list of return rates for an asset on a daily basis. Do not enter the return rates in percent values (%); use perunit values.

Once you add the columns, input the position on each asset. Set the Holding Period (trading days) and the

Confidence Level (1-).

Outputs

Descriptive statistics of each asset daily return

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16. Exponentially Weighted Moving Average (EWMA)

Forecast

ISSTAS follows the J.P. Morgan RiskMetrics approach to estimating and forecasting volatility by

exponentially weighted moving average model (EWMA).

Inputs

Choose the columns for daily return rates of each asset in a portfolio. Each of these columns must have a

list of Continuously Compounded Return for an asset on a daily basis. Do not enter the return rates in

percent values (%); use per unit values.

Order is the time order of the data series:

Ascending: the first data point the value in the first row- corresponds to the earliest date. Descending: the first data point the value in the first row- corresponds to the latest or most

recent date.

Lambda is the smoothing parameter or decay factor used for the exponential-weighting scheme. A default

value of 0.94 is shown.

Set the forecast time/horizon (t). If you set 1 as forecast time, application computes the forecast for the

next day, given the information up to and including the last day of the series.

Outputs

Descriptive statistics of each asset daily return

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For each asset, Position, One-day Expected Return, Volatility by EWMA method, One-day Value

at Risk, Total Value at Risk for n Trading Days.

One-day Covariance matrix by EWMA method.

Correlation matrix by EWMA method.

One-day Portfolio Expected Return

Portfolio Variance.

Portfolio Volatility.

One-day Value at Risk

Holding Period in Trading Days

Total Value at Riskfor n Trading Days

For each asset, Marginal Value at Risk, Component Value at Risk, Incremental Value at Risk.

Remarks

The time series is supposed homogeneous or equally spaced. Missing values are removed from theseries.

The daily returns should be computed as Continuously Compounded Return: ln(Si/Si-1).

The time series should have more than 50 values.

When computing EWMA volatility, ISSTATS assumes that the time series has an average equal

to zero; but it does not assumes the average is zero when computing the VaR (VaR = + z).

ISSTATS does not use the recursive formula for EWMA; hence it does not compute any initial

variance.

Please, check the method and assumptions at Methods and Formulas Help: Exponentially Weighted

Moving Average (EWMA) Forecast.

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Input Values

This formula takes four input variables.

High: Daily high price.

Low: Daily low price.

Close: Daily close price.

Volume: Daily volume.

Output Value

This formula outputs one variable.

AD: Accumulation distribution index.

Average True Range Formula

The average true range formula records the maximum values of the following three differences, and

calculates the moving average of the resulting data series:

Between the previous day's high and low prices.

Between the previous day's close price and the current day's high price.

Between the previous day's close price and the current day's low price.

The average true range indicator is a good measure of commitment. A high value often indicates market

bottom due to panic sell. A low value often indicates market top.

Parameters

This formula takes one optional parameter.

Period: Period for calculating the moving average of the true range values. The default value is 14.

Input Values

This formula takes one input variable.




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Input Values

This formula takes three input variables.




Output Value


EOM: Ease of movement indicator.

Envelopes Formula

The envelopes formula calculates "envelopes" above and below a moving average using a specified

percentage as the shift. The envelopes indicator is used to create signals for buying and selling. You can

specify the percentage the formula uses to calculate the envelopes.

Parameters

This formula takes two required parameters.

Period: Period for calculating the moving average.

Shift: Percentage used to shift the upper and lower envelopes from the moving.

Input Values


Price: Price for which the envelopes are calculated.

Output Value

This formula outputs two variables.

Upper: Upper envelope.

Lower: Lower envelope.

Forecasting Formula

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The triangular moving average formula takes a simple moving average of data and applies a simple

moving average on the first moving average. It is a lagging indicator, and is always behind the price. The

triangular moving average gives the most weight to the middle portion of the data.

Parameters

This formula takes one required parameter.

Period: Period for calculating the moving averages.

Input Values


Price: Price for which the triangular moving average is calculated.

Output Value


TMA: Triangular moving average.

Triple Exponential Moving Average Formula

The triple exponential moving average formula is useful for eliminating short and insignificant cycles in

the data. It smoothes the data three times using the Exponential Moving Average Formula, and then

calculates the rate of change in the moving average based on the result for the previous day.

Parameters


Period: Period for calculating the exponential moving average for the triple exponential moving

average indicator.

Input Values


Price: Price for which the triple exponential moving average indicator is calculated.

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Parameters


Start NVI: Start value of the negative volume index.

Input Values

This formula takes two input variables.



Output Value


NVI: Negative volume index.

On Balance Volume Formula

The on balance volume formula measures positive and negative volume flows.

Input Values




Output Value


OBV: On balance volume indicator.

Performance Formula

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The performance formula calculates the rate of price change compared with historical data. It differs from

the Rate of Change Formula in that it calculates rate of change against the first available data. The output

is a percentage.

This formula can also be used to calculate the rate of volume change.

Input Values


Price: Price for which the performance indicator is calculated. It can be any other data for which

you wish to calculate the performance indicator, such as volume.

Output Value


Performance: Performance indicator.

Positive Volume Index Formula

The positive volume index formula helps identify a bear market. When the positive volume index is

below its moving average there is higher probability for a bear market. The probability for a bear market

is much lower when the positive volume index is above its moving average.

This formula should be used together with the Negative Volume Index Formula.

Parameters


Start PVI: Start value of the positive volume index.

Input Values




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Output Value


PVI: Positive volume index.

Median Price Formula

The median price formula calculates the average value of daily high and low prices.

Input Values




Output Value


MP: Median price indicator.

Typical Price Formula

The typical price formula calculates the average value of daily high, low, and close prices.

Input Values





Output Value


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TP: Typical price indicator.

Weighted Close Formula

The weighted close formula calculates the average value of daily prices, but gives more weight to the

close price.

Input Values



Low: Daily low price. Close: Daily close price.

Output Value


WC: Weighted close indicator.

Price Volume Trend Formula

The price volume trend formula calculates a cumulative volume total using relative changes of the close

price. A bullish divergence between the price volume trend indicator and the price indicates that the

market is at the bottom. A bearish divergence between the price volume trend indicator and the price

indicates that the market is at the top.

Input Values




Output Value


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InnerSoft STATS - Application Manual v1.7

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