Release 4.6 Announcement

I am pleased to announce Release 4.6 of the Real Statistics Resource Pack. The new release is now available for free download (Download Resource Pack) for Excel 2010, 2013 and 2016 (Windows version) environments. It will be available tomorrow for Excel 2007 users.

The spreadsheets for all the examples used on the Real Statistics website, including those related to the new Release 4.6 features) are available for free download (Download Examples Workbooks). These are contained in three Excel files (i.e. workbooks): Examples Workbook Part 1, Examples Workbook Part 2 and Multivariate Examples. See Workbook Examples for a description of which examples are contained in which files.

The Real Statistics website is in the process of being updated to reflect the new features. These changes will be made over the next several days. In addition, I will be adding a new examples workbook, Time Series Examples, which contains the examples for the time series capabilities.

Release 4.6 contains the following new features:

Time Series Data Analysis Tools and Functions

Three new data analysis tools have been added:

Basic Forecasting: Simple Moving Average, Weighted Moving Average, Exponential Smoothing, Exponential Trend, Holt’s Linear Trend, Holt-Winter’s model

ARIMA Model: Builds autoregressive integrated moving average (aka Box-Jenkins) time series models and produces forecasts based on these models

Time Series Tests: Calculates ACF, ACVF and PACF, as well as performing the following tests: Bartlett’s, Box-Pierce, Ljung-Box and Augmented Dickey-Fuller (ADF) test.

The following new functions have also been added:

ADFCRIT(n, alpha, type) = critical value for the Augmented Dickey-Fuller test, where n = size of the time series and type = 0 (no trend, no drift), 1 (no trend, drift), 2 (trend and drift)

ADFTEST(R1,  lab, lag, criteria, type, alpha): an array function which returns a column range for the ADF test consisting of tau-stat, tau-crit, stationary (yes/no), AIC, BIC and lags, where R1 is the column range which contains the time series, criteria = “aic”, “bic” or “none” and type is as in ADFCRIT. If criteria = “none” then lag = the lag being tested; otherwise it is the largest lag being tested. If lab = True then a column of descriptive labels is appended to the output.

ARROOTS(R1): array function which outputs one row for each of the p phi coefficients in the autoregressive process (AR) listed in range R1: real part of the root, imaginary part of the root, absolute value of the root

MAROOTS(R1): array function which outputs one row for each of the q theta coefficients in an moving average process (MA) listed in range R1: real part of the root, imaginary part of the root, absolute value of the root

ADIFF(R1, d): array function which outputs the differenced version of the time series contained in range R1 based on differencing d times.

PSICoeff(R1,R2,k): array function which returns the first k coefficients of the psi representation of the ARMA process whose phi coefficients are contained in range R1 and whose theta coefficients are contained in range R2.

ARMA_SSE(R1, R2, avg, p, q) = the SSE (residual sum of squares) value for the ARMA process with mean avg whose phi coefficients are contained in range R1 and whose theta coefficients are contained in range R2, where pth phi coefficient is set to zero and/or the qth theta coefficient is set to zero.

A big thanks to Milos Cipovic, who programmed the algorithms for the Augmented Dickey-Fuller (ADF) test.

Fisher Exact Test

The Fisher Exact Test for 2 × 2 contingency tables has been expanded to support the two-tailed test for 2 × 3, 2 × 4, 2 × 5, 2 × 6, 3 × 3 and 3 × 4 contingency tables.

The FISHERTEST function now supports these new table sizes and a Fisher Exact Test option  has been added to the Chi-square Test for Independence data analysis tool.

Because these new Fisher Exact Tests are resource intensive, limits have been placed on the sum of all the cells in the contingency tables that are supported. These limits are currently set at 2,000 for a 2 × 3 table, 1,200 for a 2 × 4 table, 440 for a 2 × 5 table , 200 for a 2 × 6 table, 280 for a 3 × 3 table and 100 for a 3 × 4 contingency table. Even close to these limits the processing can be quite slow, taking about 45 seconds on my computer.

A big thanks to Paolo Cadringher, who programmed the algorithms for these new Fisher Exact Tests.

Data Analysis Tools

A small change has been made to the dialog boxes of the Real Statistics data analysis tools. If you click on any cell in the current worksheet prior to using any of the data analysis tools, that cell is used as the default location of the output. This remains as before.

Henceforth, if you highlight more than one cell, then the resulting range is used as the default Input Range value (or if there is more than one input range, then the first input range defaults to the highlighted range). In this case, the Output Range defaults to blank, which means that the output will be written to a new worksheet.

You can override any of these defaults.

Biserial Correlation Coefficient

The new BCORREL(Rx, Ry) function can be used to compute the biserial correlation function between the data in ranges Rx and Ry where Rx s a column range consisting of 0’s and 1’s.

Roots of a Polynomial

The new ROOTS array function is used to calculate the roots of any polynomial (with real coefficients). E.g. the roots of x2 – 1 are x = 1 and x = -1, while the roots of  x2 + 1 are x = i and x = –i where i = the square root of -1 (an imaginary number).

Weighted Random Values

A new weighted random value function WRAND has been added. E.g. if the range A1:A4 contains the four weights 5,1,1,3, then WRAND(A1:A4) generates a random integer value between 1 and 4 where the probability of generating a 1 is 5/(5+1+1+3) = 50%, the probability of generating a 2 is 1/(5+1+1+3) = 10%, etc.

WRANDOM is a new array function. If, for example, you want to generate two integer random values between 1 and 4 using the above weights, then you would highlight a range consisting of two cells, enter the formula =WRANDOM(A1:A4, TRUE) and press Ctrl-Shft-Enter. If you want to make sure that the two values generated are not equal (i.e. sampling without repetition), then you would enter the formula =WRANDOM(A1:A4, FALSE).

Bug Fixes

Fixes a bug that occurs when choosing the Interaction Contrast option of the Two Factor Anova Follow Up data analysis tool

Fixes a bug which occurs when choosing the Two Independent Samples option of the T Test and Nonparametric Equivalents data analysis. This bug only occurs for the non-equal variances version of the test when a non-zero Hypothetical Mean difference value is entered.

Fixes a bug when using the Royston version of the Shapiro-Wilk test for samples of size 4.

Posted in Announcement, New Release | 2 Comments

Release 4.5 Announcement

I am pleased to announce Release 4.5 of the Real Statistics Resource Pack. The new release is now available for free download (Download Resource Pack) for Excel 2007, 2010, 2013 and 2016 (Windows version) environments.

The spreadsheets for all the examples used on the Real Statistics website, including those related to the new Release 4.5 features) are available for free download (Download Examples Workbooks). These are contained in three Excel files (i.e. workbooks): Examples Workbook Part 1, Examples Workbook Part 2 and Multivariate Examples. See Workbook Examples for a description of which examples are contained in which files.

The Real Statistics website is in the process of being updated to reflect the new features. These changes will be made over the next several days.

Release 4.5 contains the following new features:

Time series analysis

In this release we initiate support for time series analysis. This work will continue in the next release as well. New functions that are available in this release are:

ACF(R1, k) – autocorrelation function of order k for the data in the column range R1

ACVF(R1, k) – autocovariance function of order k for the data in the column range R1

PACF(R1, k) – partial autocorrelation function of order k for the data in column range R1

ACOV(R1, k) – autocovariance matrix for the data in column range R1

ACORR(R1, k) – autocorrelation matrix for the data in column range R1

Bland-Altman

Bland-Altman is a method for comparing two measurements of the same variable. A Bland-Altman data analysis tool is now available, which can be accessed via the Reliability menu option.

Correlation Exact Test

The Correlation Exact Test can be used in place of the Fisher transformation approach to testing the value of the correlation coefficient. The following functions have been added:

CORRDIST(r, n, rho) – correlation distribution function (cdf) for a sample of size n with sample correlation r and population correlation rho

CORRINV(alpha, n, rho) – inverse of the correlation distribution function

CORRETEST(R1, R2, rho, tails) – p-value for the correlation exact test for the data in ranges R1 and R2, with population correlation rho and tails = 1 or 2

CORRELETEST(R1, R2, rho, lab, alpha, tails) – array function similar to CORRETEST, except that a 1-alpha confidence interval is also output

Thanks to António Teixeira who suggested this topic and contributed greatly to its development.

Skewness and Kurtosis Testing

The following array functions test whether sample data comes from a distribution which has zero skewness and/or kurtosis.

SKEWTEST(R1, lab, alpha) – array function which tests whether the skewness of the sample data in range R1 is zero (consistent with a normal distribution). The output consists of sample skewness, standard error, test statistic, p-value and 1-alpha confidence interval

KURTTEST(R1, lab, alpha) – array function which tests whether the kurtosis of the sample data in range R1 is zero (consistent with a normal distribution). The output consists of sample kurtosis, standard error, test statistic, p-value and 1-alpha confidence interval

D’Agostino-Pearson Test for Normality

The  D’Agostino-Pearson test is yet another test to determine whether data comes from a population which is normally distributed. Generally, Shapiro-Wilk will give more accurate results, but this test can be useful where the sample data has a number of repetitions.

DAGOSTINO(R1) – the test statistic s2 + k2 where s is the test statistic for skewness testing and k is the test statistic for kurtosis testing (described above).

DPTEST(R1) – p-value for the D’Agostino-Pearson test.  When the data comes from a population with a normal distribution, the D’Agostino-Pearson test statistic has a chi-square distribution with 2 degrees of freedom.

Population skewness and kurtosis functions

The follow functions have been added:

SKEWP(R1) – skewness of the distribution for the population in range R1. This is equivalent to the Excel 2013/2016 function SKEW.P, and can be useful to users with prior versions of Excel.

KURTP(R1, excess) – kurtosis of the distribution for the population in range R1. If excess = TRUE then 3 is subtracted from the result (the usual approach so that a normal distribution has kurtosis of zero).

Adjusted Correlation Coefficient and Coefficient of Determination

The following function output the usual adjusted R2 value:

RSQ_ADJ(r, n) – adjusted R2 value = 1-(1-r2)(n-1)/(n-2)  where r = the sample correlation and n = the size of the sample

RSQ_ADJ(R1, R2) – adjusted R2 value for the data in ranges R1 and R2

The following function outputs a relatively unbiased value for the population correlation coefficient. Note that this value is not the square root of the adjusted R2 value described above, and provides a better estimate of the population correlation coefficient.

CORREL_ADJ(r, n) – estimated population correlation coefficient = r[1 +(1 –r2) /2(n -3)]  where r = the sample correlation and n = the size of the sample

CORREL_ADJ(R1, R2) – estimated population correlation coefficient for the data in ranges R1 and R2

Thanks to António Teixeira who suggested this topic.

Matrices raised to a Power

For any square matrix A, A0 = the identity matrix and An+1 = AnA. The following function calculates An where A is the matrix contained in the k × k range R1.

MPOWER(R1, n) = An where A consists of the data in range R1.

We use this function with Markov chains.

Bug Fixes

The results for the Scheirer Ray Hare Test data analysis tool had an error, which produced incorrect results. This has now been corrected. Thanks for Kevin Bluxome for identifying this error.

The values for the adjusted means in the ANCOVA data analysis tool were in error. This has now been corrected. Thanks to Bill G. for identifying this error.

Posted in Announcement, New Release | 2 Comments

Suggestion for Excel 2007 Users

A number of Excel 2007 users have run into various problems when installing or running Real Statistics. Here is a suggestion from Cyberpreneur which may be helpful to you

“to correct the password problem requires installing the Real Stat addin in proper manner. Copy the downloaded file to /Microsoft Office/Office12/Library/Analysis , then restart excel. Then install in normal way.”

Charles

Posted in Hint | 1 Comment

Bug Fix Release 4.4.3

There is a new release of the Real Statistics Resource Pack, Rel 4.4.3 for Excel 2007, 2010, 2013 and 2016 environments, which corrects the following bugs:

Three Factor ANOVA data analysis tool: Fixes an incorrect p-value. Thanbks to Aaron for identifying this problem

FISHERTEST function: Fixes a bug which gave an incorrect p-value in certain situations. Thanks to Hoang for identifying this problem.

I am sorry for any inconveniences that these bugs have caused.

Charles

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Real Statistics Release 4.4.2

I have just issued a new bug fix release for the Real Statistics Resource Pack, Release 4.4.2.

This release fixes a bug in the Multiple Linear Regression data analysis tool when the without intercept option is chosen. The revised version changes the standard errors of the coefficients and the value of R-square (along with any of the other values that depend on these).

In addition, the AdjRSquare(R1, R2, con) function has been corrected in the case where con = FALSE (i.e. in the no intercept case).

Finally, I have also changed the Jenks Natural Breaks data analysis tool to use the term “Class” instead of “Break” or “Category”.

Only the version for Excel 2010 and 2013 has been released. I expect to issue the version for Excel 2007 shortly. The Real Statistics Examples Part 2 and Real Statistics Multivariate Examples files will also be updated shortly.

I expect that the Real Statistics software also functions with Excel 2016 (which was released a week ago), but it has not been tested yet. If you have used the Real Statistics Resource Pack with Excel 2016, I would appreciate your feedback.

Charles

Posted in Announcement, New Release | 2 Comments

Real Statistics Release 4.4

I am pleased to announce Release 4.4 of the Real Statistics Resource Pack. The new release is now available for free download (Download Resource Pack) for Excel 2007, 2010 and 2013 environments.

The spreadsheets for all the examples used on the Real Statistics website, including those related to the new Release 4.4 features) are available for free download (Download Examples Workbooks). These are contained in three Excel files (i.e. workbooks): Examples Workbook Part 1, Examples Workbook Part 2 and Multivariate Examples. See Workbook Examples for a description of which examples are contained in which files.

The Real Statistics website is in the process of being updated to reflect the new features. These changes will be made over the next several days.

Release 4.4 contains the following new features:

Multiple Linear Regression without Intercept

There is a new option for the Linear Regression data analysis tool which performs Multiple Linear Regression where the intercept is assumed to be zero.

To access this data analysis tool, press Ctrl-m (or choose Real Statistics Data Analysis Tools from the Add-Ins ribbon), double-click on the Regression option and then select Multiple Linear Regression. On the dialog box that appears, uncheck the Include constant (intercept) option.

There is a new array function Reg0Coeff, which is similar to the existing RegCoeff function, except that it outputs the regression coefficients and their standard errors for regression without an intercept coefficient.

The following existing functions now take a new argument con: HAT, DIAGHAT, LEVERAGEAdjRSquare, RegAIC, RegAICc, SSReg, SSRes, SSRegTot, dfRes, dfRegTot, MSReg, MSRes, MSTot, RegF, RegTest, RSquare, AdjRSquare, MultipleR, RegE, RegY. When the con argument is TRUE (default) then the regression is assumed to have an intercept, while when this argument is FALSE the regression is done assuming that the intercept is zero.

Weighted Multiple Linear Regression

There is a new data analysis tool which performs Weighted Multiple Linear Regression. This is especially useful when the homogeneous variance assumption for least squares method is not met.

To access this data analysis tool, press Ctrl-m (or choose Real Statistics Data Analysis Tools from the Add-Ins ribbon), double-click on the Regression option and then choose the Weighted Linear Regression option.

There is a new array function WRegCoeff, which is similar to the existing RegCoeff function, except that it outputs the regression coefficients and their standard errors where there are weights.

Huber-White Robust Standard Errors

The Linear Regression data analysis tool has been modified to allow you to choose a robust standard errors option. This is especially useful when the homogeneous variance assumption for least squares method is not met, and there is not enough information to use weighted linear regression.

To use this capability, press Ctrl-m (or choose Real Statistics Data Analysis Tools from the Add-Ins ribbon), double-click on the Regression option and then choose the Multiple Linear Regression option. You are presented with a choice of the following options No, HC0, HC1, HC2, HC3 and HC4.

No is the ordinary least squares option (default), which assumes that the variances are equal (called homoscedasticity). This is how we calculated the standard errors of the regression coefficients in all previous releases of the software. HC0 modifies the OLS approach in large samples to provide better estimates of the standard errors of the regression coefficients when the variances are not equal (called heteroscedasticity). The other options are used in place of HC0 with smaller samples.

There is a new array function RRegCoeff, which is similar to the existing RegCoeff function, except that it outputs the regression coefficients and their standard errors when robust standard errors are employed.

Both the Multiple Linear Regression data analysis tool and RRegCoeff function also support regression without an intercept.

Schwarz Baysean Criterion (BSC)

There is a new RegSBC function which computes the SBC for multiple linear regression. SBC is also called Schwarz Information Criterion (SIC). This function takes the form:

RegBSC(Rx, Ry, con, aug)

where Rx is a range containing the X data and Ry is a range containing the Y data. If con = TRUE (default) regression with an intercept is used and if con = FALSE regression without an intercept is used. If aug = TRUE an extra constant term n(1+LN(2π)), where n is the sample size, is added to the output (default for aug is FALSE).

The RegAIC and RegAICc functions have now been revised so that they too take con and aug arguments.

Gage R&R

There is a new Gage R&R data analysis tool which generates a Gage Repeatability and Reproducibility report that can be used to assess a measurement system using ANOVA.

To access this data analysis tool, press Ctrl-m (or choose Real Statistics Data Analysis Tools from the Add-Ins ribbon), double-click on the Analysis of Variance option and then choose Two Factor Anova which contains the Gage R&R option.

Jenks Natural Breaks

There is a new data analysis tool which performs the Jenks Natural Breaks algorithm. This is a cluster analysis method which breaks a range of values into natural categories, typically used to color maps.

To access this data analysis tool, press Ctrl-m (or choose Real Statistics Data Analysis Tools from the Add-Ins ribbon), double-click on the Multivariate Analyses option and then choose the Jenks Natural Breaks option.

Option to Disable Ctrl-m

For those of you who use the keyboard shortcut Ctrl-m for some other purpose, you can disable Crtl-m from being used as a way to display the dialog box for Real Statistics data analysis tools. In this case you will need to use choose Real Statistics Data Analysis Tools from the Add-Ins ribbon to display this dialog box.

To disable Ctrl-m, press Alt-F8 (or select View > Macros|Macros). Next insert the macro name DisableToolsShortcut in the Macro dialog box that appears and press the Run button. To enable Ctrl-m, repeat the same sequence of steps except that you need to insert EnableToolsShortcut as the macro name.

Bug Fixes

The ATEST(R1, b) function computes the p-value for one-way ANOVA where the groups are arranged in columns when b = TRUE (default) and in rows when b = FALSE. A bug has been fixed which gave the wrong p-value when b = FALSE.

When the input entries for Kaplan-Meier’s Survival Analysis which are latest in time all have a dead status, then the standard error for these entries result in division by zero. This has now been corrected.

Posted in Announcement, New Release | 2 Comments

Website Changes

You may have noticed that I have made a few minor changes to the main/home menu of the website. These consist of the following:

The Correlation menu has been relabeled the Miscellaneous menu. In addition to the Correlation and Reliability sub-menus, the Survival Analysis sub-menu has been added, and the Non-parametric Tests and Dealing with Missing Data sub-menus have been moved here.

A new Real Statistics Environment sub-menu has been added to the Basics menu. This sub-menu is under development, but should eventually provide a clearer explanation of how to use the various Real Statistics Resource Pack capabilities.

You may also have noticed that some of the Release 4.3 capabilities are now described on the website, especially regarding Kaplan-Meier Survival Analysis. Additional information will be added in the next few days.

Charles

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Release 4.3 of Real Statistics Resource Pack

I am pleased to announce Release 4.3 of the Real Statistics Resource Pack. The new release is now available for free download (Download Resource Pack) for Excel 2007, 2010 and 2013 environments.

The spreadsheets for all the examples used on the Real Statistics website, including those related to the new Release 4.3 features) are available for free download (Download Examples Workbooks). These are now contained in three Excel files (i.e. workbooks): Examples Workbook Part 1, Examples Workbook Part 2 and Multivariate Examples. See Workbook Examples for a description of which examples are contained in which files.

The Real Statistics website is in the process of being updated to reflect the new features. These changes will be made over the few days.

Release 4.3 contains the following new features:

Survival Analysis

There is a new Survival Analysis data analysis tool which provides access to the following capabilities:

  • Kaplan-Meier procedure: one and two sample versions, survival curves, log-rank test, hazard ratio, etc.
  • Cox Regression: regression analysis

In addition there are the following new array functions

COXEST: similar to Excel’s LINEST function (for multiple regression), but for Cox regression.

COXPRED: predicts the hazard ratio between two subject profiles based on a Cox regression model

LOGRANK: calculates the log-rank related statistical tools to determine whether two survival curves are statistically different.

Step Chart Data Analysis Tool

Enables you to create charts of step functions

Confidence and Prediction Intervals for Multiple Regression

The new RegPRED array function lets you to calculate the confidence and prediction intervals for multiple regression.

New Sort Functions

In addition to the existing QSORTRows function that enables you to sort a range by rows based on one key, there are now two new functions that allow you to sort by rows using a primary and secondary key.

QSORT2Rows: sorts the rows in ascending or descending order

QSORT2RowsMixed: sorts the data in ascending or descending order of the primary key, but in case of a tie it sorts the secondary key in the opposite order

Matrix Merge Function

The following new array function has been added

MERGE(R1, R2): outputs an m × n1+n2 range which contains the values in the m2 × n2 range R2 adjoined to the right of the  m1 × n1 range R1, where m = max(m1, m2) and any missing values are filled with empty cells

Shapiro-Wilk

In calculating the p-value for the original version of the Shapiro-Wilk test, harmonic interpolation is now used for values in Shapiro-Wilk table. If you prefer using linear interpolation, you can specify that h = FALSE in the following functions.

  • SWPROB(n, W, b, h) = p-value for the Shapiro-Wilk test
  • SWTEST(R1, b, h) = p-value for the Shapiro-Wilk test

Checking assumptions for Two Factor ANOVA

To make it easier to check the normality and homogeneity of variance assumptions for two factor ANOVA, a new Reformat option has been added to the Two Factor Anova data analysis tool. This option converts data in two factor Anova Excel format to one factor Anova Excel format. In this format, you can use the Descriptive Statistics and Normality (esp. Shapiro-Wilk) and Levene’s test data analysis tool capabilities to check for normality, outliers and homogeneity of variances.

Multiple Linear Regression

The RegCoeff function and the Linear Regression data analysis tool will now support more than 64 independent variables. Actually they will support as many variables as the the size of the largest matrix that can be inverted using the MINVERSE function.

Bug Fixes

  • ANCOVA data analysis tool: the SSBet value in the output has been corrected, which impacts the values of other cells in the output.
  • Two factor repeated measures ANOVA data analysis tool: The F-crit value for the Rows factor has been corrected.
Posted in Announcement, New Release | Comments Off on Release 4.3 of Real Statistics Resource Pack

Interpolation Changes

Quick Update

I have completed the updating of the website for compatibility with Release 4.2. I have also issued an update to the Examples Workbook.

One thing that I left out of the Rel 4.2 release announcement is that an argument has now been added to various table lookup functions which enables you to specify whether you want to use linear or harmonic interpolation when for values between the values provided in statistics tables.

The functions supported are RhoCRIT, TauCRIT, MCRIT, WCRIT, DCRIT, LCRIT, KSCRIT, QCRIT, DLowerCRIT, DUpperCRIT and SRankCRIT.

See Interpolation for more details.

Charles

Posted in Announcement, Hint | Comments Off on Interpolation Changes

Release 4.2 of Real Statistics Resource Pack

I am pleased to announce Release 4.2 of the Real Statistics Resource Pack. The new release is now available for free download (Download Resource Pack) for Excel 2007, 2010 and 2013 environments.

The Real Statistics Examples Workbook has been updated for compatibility with the new release and can be downloaded for free.

The Real Statistics website is in the process of being updated to reflect the new features. These changes will be made over the few days.

Release 4.2 contains the following new features:

Two Factor ANOVA Follow-up Testing

A new Two Factor ANOVA Follow-up Testing data analysis tool has been added. This tool provides Simple EffectsContrasts (planned tests) and Tukey HSD (unplanned tests) for two-dimensional data tables for analysis of main effects, simple effects and interactions.

Enhancement to the One-way ANOVA data analysis tool

An option has been added which provides access to Dunnett’s post-hoc test. This test uses a table of critical values. These can be accessed using the new DCRIT function.

Follow-up tests to Kruskal-Wallis have also been added, including ContrastsNemenyi, Dunn’s and Dunett’s tests.

The Kruskal-Wallis test now applies a ties correction factor. A new array function KW_TEST is now available which carries out this test, including a ties correction.

Effect sizes have been added to the results of the Tukey HSD test for one factor ANOVA.

Enhancements to Nonparametric tests

The Nonparametric option of the T Test and Nonparametric Equivalents data analysis tool has been modified so that the results using the normal approximation, critical values table and exact tests are more clearly labeled.

An option has also been added which enables you to add a continuity correction. This covers the Mann-Whitney and Signed-Ranks tests.

The MANN_TEST and SRANK_TEST array functions have also been modified to include a continuity correction option.

Diagonal of hat matrix

A new function DIAGHAT(R1) has been added which calculates the diagonal of the hat matrix (for multiple linear regression). The LEVERAGE function now calls this function instead of the HAT function, which means that the LEVERAGE function can now calculate leverage for very large data sets (previously limited to about 2,200 data elements).

Durbin-Watson test

The DURBIN function has been enhanced so that the normal approximation is used when there is no entry in the table of critical values. The normal approximation is based on the property that for large samples of size n, the Durbin-Watson statistic is approximately normally distributed with mean 2 and variance 4/n.

Bug Fix

The value of Cohen’s effect size in Contrasts for one-way ANOVA has been corrected.

The value for Roy’s Largest Root has been corrected in the MANOVA data analysis tool.

Posted in Announcement, New Release | 1 Comment