statistics

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InstallHelp.txt

Data Analysis Plus v9 in VBA *NOTE: For best installation results, disable 'Data Analysis' (File>Options>Add-Ins> Disable 'Analysis ToolPack') before installing DAP. (then re-enable 'Data Analysis' after installing DAP) Supported on the following versions of Excel: > Microsoft Excel 97 - 2013 on Windows OS > Office 2001 for Mac OS > Office 2004 for Mac OS Data Analysis Plus v9 in VBA: Installation Steps for Excel 2007: 1. Copy 'Stats_2007-2013_v9b.xls' to the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office12\XLSTART\Stats_2007-2013_v9b.xls') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office12\XLSTART\Stats_2007-2013_v9b.xls') 2. Copy ' Stats_2007-2013_v9b.chm' to one folder above the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office12\ Stats_2007-2013_v9b.chm') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office12\ Stats_2007-2013_v9b.chm') OR Data Analysis Plus v9 in VBA: Installation Steps for Excel 2010: 1. Copy 'Stats_2007-2013_v9b.xls' to the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office14\XLSTART\Stats_2007-2013_v9b.xls') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office14\XLSTART\Stats_2007-2013_v9b.xls') 2. Copy 'Stats_2007-2013_v9b.chm' to one folder above the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office14\Stats_2007-2013_v9b.chm') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office14\Stats_2007-2013_v9b.chm') OR Data Analysis Plus v9 in VBA: Installation Steps for Excel 2013: 1. Copy 'Stats_2007-2013_v9b.xls' to the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office15\XLSTART\Stats_2007-2013_v9b.xls') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office15\XLSTART\Stats_2007-2013_v9b.xls') 2. Copy 'Stats_2007-2013_v9b.chm' to one folder above the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office15\Stats_2007-2013_v9b.chm') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office15\Stats_2007-2013_v9b.chm') *NOTE: With Excel 2013, the 'Data Analysis' macros must be disabled to run the 'Data Analysis Plus' macros !! OR Data Analysis Plus v9 in VBA: Installation Steps for Excel 2016: 1. Copy 'Stats_2007-2013_v9b.xls' to the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\root\Office16\XLSTART\Stats_2007-2013_v9b.xls') (i.e. x64 - 'C:\Program Files\Microsoft Office\root\Office16\XLSTART\Stats_2007-2013_v9b.xls') 2. Copy 'Stats_2007-2013_v9b.chm' to one folder above the XLSTART folder. (i.e. x86 - 'C:\Program Files (x86)\Microsoft Office\Office16\Stats_2007-2013_v9b.chm') (i.e. x64 - 'C:\Program Files\Microsoft Office\Office16\Stats_2007-2013_v9b.chm') *NOTE: With Excel 2016, the 'Data Analysis' macros must be disabled to run the 'Data Analysis Plus' macros !! For additional help and support, visit www.KellerStatistics.com.

Stats_2007-2010_v9b.chm

» Bartlett's Test


Input Range:	Specify 2 or more adjacent columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Box Plot


Input Range:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.

» Chi-Squared Test and Estimate: Variance


Input Range:	Specify one column of numbers.
Hypothesized Variance:	The specified value must be greater than 0.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» Chi-Squared Test of Normality


Input Range:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» Contingency Table


Input Range:	Specify two or more equal-length columns of integers.
Labels:	Click the box if the input range’s first columns and rows contain the names of the categories.
Alpha:	Alpha must be greater than 0 and less than 1.

» Contingency Table (Raw Data)


Input Range:	Specify two adjacent equal-length columns of integers greater than 0.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Correlation


Input Range:	Specify two adjacent equal-length columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Durbin Watson Statistic


Input Range:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.

» F-Estimate: Two Variances


Input Range1:	Specify one column of numbers.
Input Range2:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» Friedman Test


Input Range:	Specify two or more adjacent equal-length columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Kruskal-Wallis Test


Input Range:	Specify two or more adjacent columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

Data Analysis Plus v9.0


This help file has been compiled to assist users of the Data Analysis Plus v9.0 macros for Microsoft Excel. Use the table of contents or index functions to locate a help information for a specific macro.

Last Updated on January 22, 2010

» Multiple Comparisons


Input Range:	Specify two or more adjacent columns of numbers.
Labels:	Click the box if the input range’s first row contains the name(s) of the variable(s).
Alpha:	Alpha must be greater than 0 and less than 1.

» Prediction Interval


Input Y Range:	Specify one column of numbers representing the dependent variable.
Input X Range:	Specify one or more adjacent equal-length columns whose number of rows equals the number of rows in the Input Y Range.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Given X Range:	Specify the given value for each independent variable. The number of values must equal the number of columns in the Input X Range.
Confidence Level (1-Alpha):	1-Alpha must be greater than 0 and less than 1.

» Seasonal Indices


Input Range:	Specify two adjacent equal-length columns of numbers. The first column is the time series in sequential order and the second column specifies the season.
Labels:	Click the box if the input range’s first row contains the name(s) of the variable(s).

» Sign Test


Input Range:	Specify two adjacent equal-length columns of numbers.
Labels:	Click the box if the input range’s first row contains the name(s) of the variable(s).
Alpha:	Alpha must be greater than 0 and less than 1.

» Statistical Process Control


XBAR (Using S), XBAR (Using R), S, and R charts
Input Range:	Specify one column of numbers
Sample size:	The sample size must be greater than or equal to 2 and less than or equal to 25. The number of rows of data in the input range must be divisible by the sample size.

P Chart
Input Range:	Specify one column of integers.
Sample Size:	The sample size must be larger than the largest integer in the input range.
Labels:	Click the box if the input range’s first row contains the name of the variable.

» Stem & Leaf


Input Range:	Specify one column of positive numbers.
Increment:	Click one of the increment values. The increment is the difference between stems.
Labels:	Click the box if the input range’s first row contains the name(s) of the variable(s).

» Stepwise Regression


No Help is available for this topic.

» Technique Identification


A series of questions designed to lead to the appropriate technique.

» t-Test and Estimate: Mean


Input Range:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» t-Estimate: Two Mean


Input Range1:	Specify one column of numbers.
Input Range2:	Specify one column of numbers.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» Wilcoxon Rank Sum Test


Input Range:	Specify two adjacent columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Wilcoxon Signed Rank Sum Test


Input Range:	Specify two adjacent equal-length columns of numbers.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Z-Estimate: Mean


Input Range:	Specify one column of numbers.
Standard Deviation (SIGMA):	Specify the value of the population standard deviation. It must be greater than 0.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Confidence Level (1-Alpha):	1-Alpha must be greater than 0 and less than 1.

» Z-Test: Mean


Input Range:	Specify one column of numbers.
Standard Deviation (SIGMA):	Specify the value of the population standard deviation. It must be greater than 0.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

» Z-Test and Estimate: Two Proportions


Input Range:	Specify two adjacent columns of integers.
Code for Success:	This value must be an integer.
Hypothesized Difference:	This value must greater than -1 and less than +1.
Labels:	Click the box if the input range’s first rows contain the names of the variables.
Alpha:	Alpha must be greater than 0 and less than 1.

» Z-Test and Estimate: Proportion


Input Range:	Specify one column of integers.
Code for Success:	This value must be an integer.
Hypothesized Proportion:	This value must be greater than 0 and less than 1.
Labels:	Click the box if the input range’s first row contains the name of the variable.
Alpha:	Alpha must be greater than 0 and less than 1.

Stats_2007-2013_v9b.xls

RangeData

18	27	32.8	37.1	40.4	43.1	45.4	47.4	49.1	50.6	52	53.2	54.3	55.4	56.3	57.2	58	58.8	59.6
6.08	8.33	9.8	10.9	11.7	12.4	13	13.5	14	14.4	14.7	15.1	15.4	15.7	15.9	16.1	16.4	16.6	16.8
4.5	5.91	6.82	7.5	8.04	8.48	8.85	9.18	9.46	9.72	9.95	10.2	10.3	10.5	10.7	10.8	11	11.1	11.2
3.93	5.04	5.76	6.29	6.71	7.05	7.35	7.6	7.83	8.03	8.21	8.37	8.52	8.66	8.79	8.91	9.03	9.13	9.23
3.64	4.6	5.22	5.67	6.03	6.33	6.58	6.8	6.99	7.17	7.32	7.47	7.6	7.72	7.83	7.93	8.03	8.12	8.21
3.46	4.34	4.9	5.3	5.63	5.9	6.12	6.32	6.49	6.65	6.79	6.92	7.03	7.14	7.24	7.34	7.43	7.51	7.59
3.34	4.16	4.68	5.06	5.36	5.61	5.82	6	6.16	6.3	6.43	6.55	6.66	6.76	6.85	6.94	7.02	7.1	7.17
3.26	4.04	4.53	4.89	5.17	5.4	5.6	5.77	5.92	6.05	6.18	6.29	6.39	6.48	6.57	6.65	6.73	6.8	6.87
3.2	3.95	4.41	4.76	5.02	5.24	5.43	5.59	5.74	5.87	5.98	6.09	6.19	6.28	6.36	6.44	6.51	6.58	6.64
3.15	3.88	4.33	4.65	4.91	5.12	5.3	5.46	5.6	5.72	5.83	5.93	6.03	6.11	6.19	6.27	6.34	6.4	6.47
3.11	3.82	4.26	4.57	4.82	5.03	5.2	5.35	5.49	5.61	5.71	5.81	5.9	5.98	6.06	6.13	6.2	6.27	6.33
3.08	3.77	4.2	4.51	4.75	4.95	5.12	5.27	5.39	5.51	5.61	5.71	5.8	5.88	5.95	6.02	6.09	6.15	6.21
3.06	3.73	4.15	4.45	4.69	4.88	5.05	5.19	5.32	5.43	5.53	5.63	5.71	5.79	5.86	5.93	5.99	6.05	6.11
3.03	3.7	4.11	4.41	4.64	4.83	4.99	5.13	5.25	5.36	5.46	5.55	5.64	5.71	5.79	5.85	5.91	5.97	6.03
3.01	3.67	4.08	4.37	4.59	4.78	4.94	5.08	5.2	5.31	5.4	5.49	5.57	5.65	5.72	5.78	5.85	5.9	5.96
3	3.65	4.05	4.33	4.56	4.74	4.9	5.03	5.15	5.26	5.35	5.44	5.52	5.59	5.66	5.73	5.79	5.84	5.9
2.98	3.63	4.02	4.3	4.52	4.7	4.86	4.99	5.11	5.21	5.31	5.39	5.47	5.54	5.61	5.67	5.73	5.79	5.84
2.97	3.61	4	4.28	4.49	4.67	4.82	4.96	5.07	5.17	5.27	5.35	5.43	5.5	5.57	5.63	5.69	5.74	5.79
2.96	3.59	3.98	4.25	4.47	4.65	4.79	4.92	5.04	5.14	5.23	5.31	5.39	5.46	5.53	5.59	5.65	5.7	5.75
2.95	3.58	3.96	4.23	4.45	4.62	4.77	4.9	5.01	5.11	5.2	5.28	5.36	5.43	5.49	5.55	5.61	5.66	5.71
2.92	3.53	3.9	4.17	4.37	4.54	4.68	4.81	4.92	5.01	5.1	5.18	5.25	5.32	5.38	5.44	5.49	5.55	5.59
2.89	3.49	3.85	4.1	4.3	4.46	4.6	4.72	4.82	4.92	5	5.08	5.15	5.21	5.27	5.33	5.38	5.43	5.47
2.86	3.44	3.79	4.04	4.23	4.39	4.52	4.63	4.73	4.82	4.9	4.98	5.04	5.11	5.16	5.22	5.27	5.31	5.36
2.83	3.4	3.74	3.98	4.16	4.31	4.44	4.55	4.65	4.73	4.81	4.88	4.94	5	5.06	5.11	5.15	5.2	5.24
2.8	3.36	3.68	3.92	4.1	4.24	4.36	4.47	4.56	4.64	4.71	4.78	4.84	4.9	4.95	5	5.04	5.09	5.13
2.77	3.31	3.63	3.86	4.03	4.17	4.29	4.39	4.47	4.55	4.62	4.68	4.74	4.8	4.85	4.89	4.93	4.97	5.01

PredIntHlp

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Prediction Interval Help

This procedures requires a single column of data for the dependent variable, one or more columns of data for the independent variables, a row of data containing the values for the predicting independent variables, and a confidence level.

The number of columns in the row for the predicting independent variables must match the number of columns for the independent variables.

Code

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CHART CONSTRUCTION

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Create the chart

Use the chart

Code2

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ESTIMATE OF SIGMA

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Use the sample standard deviation.

Use the range (largest - smallest).

Tech

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STATISTICAL PROCESS CONTROL

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XBAR Chart

S Chart

R Chart

P Chart

SPC

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TECHNIQUE IDENTIFICATION

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This macro was created to help you determine the appropriate statistical inference procedure to use to address a specific problem. It consists of a series of questions whose answers identify the correct technique.

We start by asking what is the purpose of the statistical technique. Click OK to continue.

Spc3Dia

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TECHNIQUE IDENTIFICATION

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To describe a single population

To analyze the relationship among two or more variables

To analyze the relationship between two variables

To compare two or more populations

To compare two populations

Help

Click one of the following answers or click HELP for more information.

What is the problem objective?

XDialog

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HELP

Analyze the problem and determine why the study was conducted. To help determine the problem objective clearly describe the population(s) or variables with which you are dealing.

For example, if you want to determine whether a new machine is superior to an older machine in that it can produce units faster and better, the problem objective is to compare two populations.

The first population is the production from the old machine and the second population is the production from the new machine.

SpcDialog

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TECHNIQUE IDENTIFICATION

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Quantitative data (Interval or ratio scale)

Qualitative data (Nominal scale)

Ranked data (Ordinal scale)

Help

Click one of the following answers or click HELP for more information.

What type of data do we have? (What is the data scale?)

Screen1

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HELP

Put yourself in the position of the statistician who gathered the data. Think about how the original data were recorded. Did you record a real number such as weight, height, or volume, in which case the data are quantitative.

If you recorded some sort of rating such as you might rate how easy it is to learn a new computer package (Responses: very easy, somewhat easy, somewhat difficult, or very difficult) the data are ranked.

Finally, if the responses are categories such as marital status or occupation, which you recorded as an arbitrarily chosen number, the data are qualitative.

ForkA

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TECHNIQUE IDENTIFICATION

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Central location

Variation

Help

Click one of the following answers or click HELP for more information.

Which characteristic of the population are you interested in?

HelpA

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TECHNIQUE IDENTIFICATION

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Yes

(Note that in the most realistic applications the population variance is unknown.)

Is the population variance known?

ForkB

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TECHNIQUE IDENTIFICATION

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Two

Two or more

Help

Click one of the following answers or click HELP for more information.

How many categories are there?

HelpB

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HELP

How many possible responses were there to the question? If there were more than two, are we interested in only one of them? If so, we would call that category a "success" and all others "failures". In that case there are only two categories.

To illustrate suppose that we ask people to report their marital status and the responses are single, married, divorced, widowed, and other. There are 5 categories.

However, if we're only interested in counting the number of married people we would have only 2 categories; married or not married.

ForkA1B1

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TECHNIQUE IDENTIFICATION

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Independent samples

Matched pairs

Help

Click one of the following answers or click HELP for more information.

What is the experimental design?

A1B11

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HELP

How were the data gathered? Did you draw independent samples from the two populations? For samples to be independent there must be no relationship between the observations in one sample and the observations in the second sample.

Matched pairs sample data are recorded such that there is a logical reason to compare the first observation in sample 1 with the first observation in sample 2, the second observation in sample 1 with the second observation in sample 2, and so on.

ForkA1B3

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TECHNIQUE IDENTIFICATION

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Yes

Click one of the following answers or click HELP for more information.

Are the data normally distributed?

Help

HelpA1B3

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TECHNIQUE IDENTIFICATION

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Yes

Click one of the following answers or click HELP for more information.

Are the population variances equal?

Help

A2B11

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TECHNIQUE IDENTIFICATION

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Independent samples

Blocks

Click one of the following answers or click HELP for more information.

What is the experimental design?

Help

HelpA2B11

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HELP

How were the data gathered? Did you draw independent samples from the k populations? For samples to be independent, there must be no relationship between the observations in the samples.

Blocked sample data are recorded in such a way that there is a logical reason to compare the first observations in samples 1,2,...,k, the second observations in samples 1,2,...,k, and so on.

A2B111

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TECHNIQUE IDENTIFICATION

Techniques: t-test and estimators of the coefficients, t-test of the coefficient of correlation, prediction interval, and interval estimator of the expected value of 'y'.

Parameters: Simple linear regression coefficients, coefficients of correlation and determination.

A2B111y

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INFERENCE

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Test of Hypothesis (Case 1)

Test of Hypothesis (Case 2)

Interval Estimate

A3B1

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INFERENCE

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Test Of Hypothesis

Interval Estimate

HelpA3B1

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ALTERNATIVE HYPOTHESIS

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ForkA4B1

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Data Analysis Plus

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Label 6

Input Range:

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InfDialog2

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Prediction Interval

Please enter the block coordinates of the given values of the independent variables:

Please enter the block coordinates of the independent variable:

Please enter the block coordinates of the dependent variable:

Specify the confidence level (1-ALPHA)

$A$2:$A$101

$B$2:$B$101

$A$102

0.95

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Help

InfDialog

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Data Analysis Plus

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Stats Macros

TIP: Try selecting your data before choosing a macro. This alters the default settings in the next display window.

Help

AltHyp

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Check for missing values?

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This procedure can check for missing values, but it takes a lot of time. If you're sure there are no missing values in the variables you're using in the regression analysis, keep the box below checked. It will speed things up considerably.

Don't check for missing values

DialogIn

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Variable name problem

1. Start each variable name with a letter or an underscore ( _ ).

2. Don't use entirely numerical names, such as 10.

3. Don't use names that are the same as cell addresses, such as X1 or AB6.

4. You can use single letter names, such as X, but you can't use R or C.

5. Avoid using symbols other than letters, numbers, and underscores.

6. Blanks are OK, but this add-in will change them to underscores.

There is a problem with at least one of your variable names. It might be that your cursor is not inside your data set. Check this first. If this isn't the problem, check that your variable names adhere to the following conventions:

PredIntDlg

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Variable selection for explanatory variables

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Select one or more explanatory variables:

Note: At this stage, select all variables that you MIGHT want to include in the regression equation. The procedure will select the ones (from this set) that end up in the regression equation.

Dialog2

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Location of results

New worksheet

Same worksheet as the data

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Where would you like your results?

Note: If you select the first option, the results are entered in newly inserted columns just to the right of your data range. If you select the second, the results begin in cell A1 of the new worksheet.

Enter name of new sheet: Enter name of new worksheet

Caution: If a worksheet with this name already exists, it will be replaced.

MissDlog

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Getting started with StepwiseRegression procedure

Continue

Quit

Help

Check that the cursor is positioned somewhere within your data set. If it isn't, click on the Quit button, position the cursor correctly, and run this procedure again.

BadNameDlog

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Stepwise regression parameters

p-values

F-values

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You indicate how significant variables need to be for entering or staying in the regression equation in one of two ways:

1. By selecting p-values for entering and leaving. The lower the p-values, the more significant a variable has to be to enter or stay in the equation. Typical values are .01, .05, or .10.

2. By selecting F-values for entering and leaving. The larger the F-values, the more significant a variable has to be to enter or stay in the equation. Typical values are from 2.5 to 4.

Significance option

VarDlog

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Stepwise regression parameters

0.05

0.1

Cancel

Now enter the values for entering and leaving, or click on OK to accept the default values. (These are the default values used by the popular SPSS statistical package.)

Several notes:

p-to-enter:

p-to-leave:

1. To prevent endless cycling, the p-to-enter value cannot be larger than the p-to-leave value.

2. To force all variables to enter, set both p-values to 1.

LocDlog

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Diagnostic options

Fitted values versus actual Y values

Fitted values versus X values(one plot for each X)

Residuals versus fitted values

Residuals versus actual Y values

Residuals versus X values(one plot for each X)

Columns of fitted values and residuals

Cancel

You can select from any of the following scatterplots:

Note: If you select the following option, two new variables will be appended to your data set.

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