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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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
You can also call us (Spain number phone):
There are different payment methods that you can find at:
http://isstats.itspanish.org/
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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Available statistics are
Mean of values Median of values
Mode of values
Number of values
Sum of values
Standard deviation
Variance
Minimum value
Maximum value
Cumulative sum
Available type charts are
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.
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.
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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Available statistics are
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.
Available type charts are
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.
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.
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.
Available type charts are
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
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. 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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http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/1_sample_t_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Mean_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/population_and_samples_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/population_and_samples_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Mean_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/1_sample_t_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm'); -
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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%.
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.
10.3. 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
Data: Choose the origin of the data.
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.
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%.
Perform hypothesis test:Check to perform the hypothesis test.
Hypothesized variance:Enter the test variance 20.
Alternative hypothesis: Choose the alternative hypothesis of the test.
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http://bsscpopup%28%27../Shared_GLOSSARY/1_variance_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/1_variance_test_def.htm'); -
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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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http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm'); -
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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
Data: Choose the origin of the data.
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.
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%.
Perform hypothesis test:Check to perform the hypothesis test.
Hypothesized mean:Enter the hypothesized difference between the two population means 1-2.
Alternative hypothesis: Choose the alternative hypothesis of the test.
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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http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Mean_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/St_dev_def.htm');http://bsscpopup%28%27../shared_glossary/Subscripts_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../shared_glossary/Subscripts_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/St_dev_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Mean_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm'); -
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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
Data: Choose the origin of the data.
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.
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%.
Perform hypothesis test:Check to perform the hypothesis test.
Hypothesized mean:Enter the hypothesized population mean of the paired differences d.
Alternative hypothesis: Choose the alternative hypothesis of the test.
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http://bsscpopup%28%27../Shared_GLOSSARY/paired_t_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/sample_size_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/independent_sample_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/paired_t_test_def.htm'); -
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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
Data: Choose the origin of the data.
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.
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%.
Perform hypothesis test:Check to perform the hypothesis test.
Hypothesized ratio:Enter the hypothesized ratio between two populations variances 21/22.
Alternative hypothesis: Choose the alternative hypothesis of the test.
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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http://bsscpopup%28%27../Shared_GLOSSARY/2_variances_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Subscripts_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Subscripts_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/Variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/confidence_interval_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/hypothesis_test_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/2_variances_test_def.htm'); -
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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
Data: Choose the origin of the data.
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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http://bsscpopup%28%27../Shared_GLOSSARY/analysis_of_variance_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/response_and_predictor_variables_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/response_and_predictor_variables_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/factor_and_factor_level_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/factor_and_factor_level_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/response_and_predictor_variables_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/response_and_predictor_variables_def.htm');http://bsscpopup%28%27../Shared_GLOSSARY/analysis_of_variance_def.htm'); -
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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
In the box Test Type, choose the test to perform:
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
In the box Test Type, choose the test to perform:
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.
High: Daily high price.
Low: Daily low price.
Close: Daily close price.
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Input Values
This formula takes three input variables.
High: Daily high price.
Low: Daily low price.
Volume: Daily volume.
Output Value
This formula outputs one variable.
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
This formula takes one input variable.
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
This formula takes one input variable.
Price: Price for which the triangular moving average is calculated.
Output Value
This formula outputs one variable.
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
This formula takes one required parameter.
Period: Period for calculating the exponential moving average for the triple exponential moving
average indicator.
Input Values
This formula takes one input variable.
Price: Price for which the triple exponential moving average indicator is calculated.
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Parameters
This formula takes one required parameter.
Start NVI: Start value of the negative volume index.
Input Values
This formula takes two input variables.
Close: Daily close price.
Volume: Daily volume.
Output Value
This formula outputs one variable.
NVI: Negative volume index.
On Balance Volume Formula
The on balance volume formula measures positive and negative volume flows.
Input Values
This formula takes two input variables.
Close: Daily close price.
Volume: Daily volume.
Output Value
This formula outputs one variable.
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
This formula takes one input variable.
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
This formula outputs one variable.
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
This formula takes one required parameter.
Start PVI: Start value of the positive volume index.
Input Values
This formula takes two input variables.
Close: Daily close price.
Volume: Daily volume.
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Output Value
This formula outputs one variable.
PVI: Positive volume index.
Median Price Formula
The median price formula calculates the average value of daily high and low prices.
Input Values
This formula takes two input variables.
High: Daily high price.
Low: Daily low price.
Output Value
This formula outputs one variable.
MP: Median price indicator.
Typical Price Formula
The typical price formula calculates the average value of daily high, low, and close prices.
Input Values
This formula takes three input variables.
High: Daily high price.
Low: Daily low price.
Close: Daily close price.
Output Value
This formula outputs one variable.
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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
This formula takes three input variables.
High: Daily high price.
Low: Daily low price. Close: Daily close price.
Output Value
This formula outputs one variable.
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
This formula takes two input variables.
Close: Daily close price.
Volume: Daily volume.
Output Value
This formula outputs one variable.
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