Release 5.3.2

Yesterday I issued a new bug fix release (Rel 5.3.2) of the Real Statistics software. This fixed an error in the F_DIST_RT function which made this function always output a value of zero. Unfortunately, this caused quite a few other Real Statistics capabilities to give incorrect results (MANOVA, ICC Power, Welch’s Test, Box Test, etc.).

This error is not present in the version of Real Statistics for Excel 2002 and 2003 users, nor for the old Rel 3.5.3 version for the Mac. I suggest that everyone else upgrade to Release 5.3.2.

I apologize for any inconvenience that I have caused you.

Charles

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Release 5.3.1

Release 5.3.1 of the Real Statistics Resource Pack is being issued today.

It contains some bug fixes for the Ridge regression data analysis tool and functions. If you have already upgraded to Rel 5.3 and don’t have any need for Ridge regression, then you don’t need to install this release.

This release is now available for Excel 2011, 2013 and 2016 (Mac and Windows) users. It will shortly be made available to Excel 2007 and 2010 users. The Examples Workbook Part 2 will also shortly be revised to support the changes in this release.

In addition to the bug fixes, the following new functions are available:

RidgeCoeff: outputs the unstandardized Ridge regression coefficients

RidgeLambda: outputs an estimated lambda value based on making sure that the VIF values are below some user-defined threshold

RidgeMSE: outputs the MSE value for a Ridge regression model

RidgePred: outputs the predicted y values corresponding to and array of x data based on a Ridge regression model

In addition to these Ridge regression functions, the release adds the following function:

RegPredCC: outputs the predicted y values for any regression model given the x values and regression coefficients. This is similar to the pre-existing RegPredC function, except that now an array of x values can be specified.

Charles

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Release 5.3 for Mac Users

Release 5.3 is now available for Mac users. This adds all the new features from Rel 5.1, 5.2 and 5.3 previously released for Windows users.

The new release is actually called 5.3.1 since it has some bug fixes for Rel 5.3 (plus a couple of new features). This release will also be available to Windows users shortly.

Charles

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Real Statistics Release 5.3

I am pleased to announce Release 5.3 of the Real Statistics Resource Pack. The new release is now available for free download at Download Resource Pack for Excel 2013 and 2016 (Windows version) environments. The resource pack for Excel 2007 and 2010 environments will be available later today or tomorrow. The resource pack for Excel 2011 and 2016 Mac environments will be available in a few days.

The various examples workbooks have also been updated for capability with the new release. The Real Statistics website will be updated over the course of the next several days to reflect the new capabilities.

Also thanks to all of you who have given donations to help sustain the Real Statistics project. This is most appreciated as are the countless number of people who have identified errors and who have made suggestions to improve the software and website.

The following is a summary of the new features in Release 5.3.

Ridge Regression

A new Ridge Regression data analysis tool has been added that performs Ridge regression, which is especially useful to handle multicollinearity.

Supporting this new tool are the following new functions:

RidgeRegCoeff: calculates the Ridge regression coefficients and standard errors.

RidgeRSQ: calculates the R-square value for Ridge regression.

RidgeVIF: calculates the VIF values for the independent variables.

RidgeCVError: calculates the Ridge regression k-fold cross-validation error for a particular value of lambda; used to estimate a desirable lambda value.

LASSO Regression

A new LASSORegCoeff function has been added to estimate the LASSO (least absolute selection and shrinkage operator) regression coefficients using a cyclical coordinate descent algorithm.

Standardized Regression coefficients

The following functions have been added:

STDCOL: takes an array or cell range and outputs an array that has the same dimensions but with a standardization of the values in each column.

StdRegCoeff: outputs the regression coefficients that corresponds to the standardization of the x and y input data.

UnstdRegCoeff: does the reverse of StdRegCoeff by outputting the unstandardized regression coefficients when the standardized regression coefficients are known.

These functions are used in performing Ridge regression.

Multiple Regression Solver option

The algorithm that performs multiple linear regression calculates (XTX)-1 where X is the design matrix. Ridge and LASSO regression are used when XTX is not invertible or when it is close to not being invertible (such as when there is multicollinearity or when there are more independent variables than data elements.

Sometimes (XTX)-1 can’t be calculated accurately in Excel because of an overflow error. This can occur when there are a large number of independent variables. In such cases, the results from the Multiple Linear Regression data analysis tool will be strange (e.g. R-square value larger than one or a negative value for SSE).

A new Use Solver option has now been added to the Multiple Linear Regression data analysis tool to handle such situations.

Cochran-Mantel-Haenszel Test

A Cochran-Mantel-Haenszel Test data analysis tool has been added. This test determines whether the odds ratios of a series of 2 × 2 contingency tables are significantly different from one. The data analysis tool also includes Woolf’s Heterogeneity test which determines whether the odds ratios are significantly different.

The analysis tool uses the following new array functions: CMHTest and WoolfTest.

Sphericity Tests

The following two tests for sphericity have been added:

MauchlyTest(R1) = p-value of Mauchly’s test for sphericity on the data in range R1

JNSTest(R1) = p-value of the John-Nagao-Sugiura test for sphericity on the data in range R1

Partitions

The following functions partitions the numbers 1 through n into k approximately equal-sized groups.

RandPart(n, k): random partition

OrderedPart(n, k): ordered partition

SortedPart(n, k, R1): ordered partition based on the sort order in the column range R1 with n

E.g. OrderedPart(10,3) outputs a column array with 10 rows containing the values 1, 2, 3, 1, 2, 3, 1, 2, 3, 1 (in that order). RandPart(10,3) outputs a column array with values such as 2, 1, 1, 3, 2, 1, 2, 3, 1, 3 (the values 2 and 3 are repeated 3 times and 1 is repeated 4 times). If R1 is a column range with the values 1.1, -1.4, 2.5, 3.6, 0.5, then SortedPart(R1,3) outputs a column range with the values 3, 1, 1, 2, 2 (in that order).

Chi-square Independence Test enhancement

The Chi-square Independence Test data analysis tool supports two input formats: Excel format (in the form of a contingency table) and Standard format. The Standard format is a two column range specifying pairs of headings for the contingency table. Thus if this range contains say 10 rows then the sum of all the cells in the contingency table would be 10.

A new version of the standard format is now also supported. It consists of three columns, the first two columns are as in the previous version, while the third column contains non-negative integer values, specifying how many times the pairs in the first two columns are to be repeated. The total cell count in the contingency table now equals the sum of the values in the third column. Also, the two column version of the standard format is equivalent to the three column version where the third column contains all ones.

Descriptive Statistics and Normality enhancement

When the Shapiro-Wilk option is chosen from the Descriptive Statistics and Normality data analysis tool, in addition to the Shapiro-Wilk test, the results of the d’Agostino-Pearson test for normality are also displayed.

Sort rows enhancements

  • Changed the QSORTRows and QSORT2Rows functions so that they properly sort rows with an empty cell in the column with the sort key(s).
  • These functions as well as QSORT2RowsMixed now retain the original order in case of ties.
  • All three functions now take an optional last argument that ensures that a header row is not sorted but remains in the first row.

Other enhancements

  • BOXCOX(R1) and BOXCOXLambda(R1) now work properly even when range R1 contains non-positive values (solves an issue for Luciano).
  • Additional error checking has been added to some of the data analysis tools.
  • The Correlation and Multivariate function categories have been added and many more functions are now supported by the Paste Function (fx) button on the Formula bar (in the Excel 2010, 2013 and 2016 (Windows) versions of the software.
  • If the Input Range Y field in the dialog box for the Multiple Linear Regression data analysis tool is not filled in, then the last column in the Input Range X field is used as the y values.
  • The Regression option of the Two Factor ANOVA data analysis tool now supports models without replications.

Bug Fixes

  • Fixed TiesCorrection in the one-sample case (thanks to Uwe for identifying this error)
  • Fixed KSCRIT and KSPROB (thanks to Daniel for identifying this error)
  • Fixed F_DIST in the pdf case (thanks to Antonio for identifying this error)
  • Fix error in the Basic Forecasting data analysis tool when output is displayed on a new worksheet
  • Fixed a bug in the CorrTest function
  • The Reformat for Linear Regression option of the ARIMA Model and Forecast data analysis tool now uses the correct input data
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Release 5.2

I am pleased to announce Release 5.2 of the Real Statistics Resource Pack. The new release is now available for free download at Download Resource Pack for Excel 2007, 2010, 2013 and 2016 (Windows version) environments.

The example files Examples Workbook Part 2 and Time Series Examples been updated for compatibility with Release 5.2.

The Real Statistics website will be updated over the course of the next few days to reflect the new capabilities in Release 5.2.

The following is a summary of the new features in Release 5.2.

ARIMA Enhancements

A new ARIMA_Coeff array function has been added which calculates the coefficients of an Arima(p, q, d) model, along with the standard errors of these coefficients and confidence intervals.

In addition, the ARIMA_Stats array function has been added which calculates various statistics (LL, SSE, MSE, AIC, etc.) for an Arima model.

Please join me in thanking Miloš Cipovic, who did a beautiful job of programming the algorithms for these new functions using the Levenberg-Marquardt method.

Minor changes

Used F_DIST_RT function in the Repeated Measures ANOVA data analysis tool to increase accuracy.

Corrected some tooltips on some dialog boxes

Added Nonparametric and TimeSeries function categories to make it easier to get information about more Real Statistics functions via the Insert Function fx capability.

The COCHRAN and QTEST formulas have been enhanced. A third argument has been added which allows you to specify that a continuity correction will be used in the case where there are only two variables (this is also the default), i.e. the case which is equal to McNemar’s test.

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More about Release 5.1

In the description of the new Release 5.1 features, I forgot to mention something which a number of people have asked for, namely

Follow-up Analyses after Three Factor ANOVA

A new ANOVA Follow-up data analysis tool has been added. This tool allows the user to perform Contrast and Tukey HSD (or Tukey-Kramer) analyses after Three Factor ANOVA.

This tool can be used with both balanced and unbalanced models and can actually be employed after any type of ANOVA (not just Three Factor ANOVA) provided you have the appropriate descriptive data and the values of MSE and dfE created by any omnibus ANOVA data analysis tool.

Quick Update

Release 5.1 is now available for users of Excel 2007, 2010, 2013 and 2016 (Windows). All the examples files have been updated and good progress has been made updating the website for compatibility with Rel 5.1. In particular, the website now includes webpages on the new ANOVA Follow-up data analysis tool as well as 2^k Factorial Design and Correspondence Analysis.

I had originally planned to improve the ARIMA support in Rel 5.1, but was unable to get it tested in time. This feature will be included in the next release.

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Real Statistics Release 5.1

I am proud to announce Release 5.1 of the Real Statistics Resource Pack, which is loaded with a lot of new features. The new release is now available for free download at Download Resource Pack for Excel 2013 and 2016 (Windows version) environments. The resource pack for Excel 2007 and 2010 environments will be available within the next 24 hours.

The example files Examples Workbook Part 1A, Examples Workbook Part 1B, Examples Workbook Part 2 and Multivariate Examples been updated for compatibility with Release 5.1.

The Real Statistics website will be updated over the course of the next several days to reflect the new capabilities in Release 5.1.

Also thanks to all of you who have given donations to help sustain the Real Statistics project. This is most appreciated as are the countless number of people who have identified errors and who have made suggestions to improve the software and website.

The following is a summary of the new features in Release 5.1.

Poisson Regression

A new Poisson Regression data analysis tool has been added that performs regression where the dependent variable contains count data.

Supporting this new tool are the following new functions: PoissonCoeff to calculate the regression coefficients and standard errors, PoissonCov to output the coefficient covariance matrix, and PoissonPred, PoissonPredC and PoissonPredCC to make predictions based on a Poisson regression model.

Correspondence Analysis

A new Correspondence Analysis multivariate data analysis tool has been added. Correspondence analysis plays a role similar to factor analysis or principal component analysis for categorical data expressed as a contingency table. The new tool will carry out the analysis and produce correspondence analysis plots.

Supporting this new tool are the following new functions: CARowFactors and CAColFactors, which return factor vectors (for the original data as well as for supplementary profiles) and CAEigen, which returns the eigenvalues for the correspondence analysis.

2^k Factorial Design

A new 2^k Factorial Design data analysis tool has been added to support ANOVA consisting of any number of factors, each of which has two levels.

Supporting this new tool are the following new functions: Design2k and ExpandDesign2k, which automatically create the coding for such designs, Effect2k, which calculates the effect sizes for 2^k factorial designs, and SS2k, which calculates the SS (sum of squares) values for these designs.

Tukey HSD and Tukey-Kramer Tests

The existing Tukey HSD and Tukey-Kramer options to the ANOVA: Single Factor data analysis have been revised. Instead of having to manually perform separate comparison tests, all possible pairwise comparisons are performed automatically. This approach will be be adopted for other ANOVA follow up tests in future releases.

One Factor ANOVA data analysis tool

The layout of the ANOVA: Single Factor dialog box has been revised to make the various options clearer and consistent with other data analysis dialog boxes. In addition, the Dunnett-KW test option (a Kruskal-Wallis follow-up test) has been renamed the Steel test. A new Kruskal-Wallis follow-up test has also been added called the Schaich-Hamerle test.

New functions for t, F and chi-square distributions

Excel’s T.DIST, F.DIST and CHISQ.DIST functions (as well as the related functions and their Excel 2007 equivalents) round down the degrees of freedom to the next lower integer. This can be a problem in some situations, and so we previously introduced the F_DIST and CHISQ_DIST functions which work exactly like F.DIST and CHISQ.DIST except that they don’t round off non-integer degrees of freedom, thereby improving the accuracy of some calculations.

We have now added the following functions which provide similar advantages: T_DIST_RT, T_DIST_2T, T_INV, T_INV_2T, F_DIST_RT, F_INV, F_INV_RT, CHISQ_DIST_RT, CHISQ_INV and CHISQ_INV_RT. In addition, we have enhanced the existing T_DIST function so that it too doesn’t round off the degrees of freedom.

Two sample correlation tests with dependent samples

The Real Statistics already provides the Correl2Test function to test whether two sample pairs drawn independently have significantly different correlations. We now add similar support in the case where the two sample pairs are not independent. In particular, we support two such cases.

In the first case, the two sample pairs have one variable in common. The new array functions Correl2OverlapTTest, Corr2OverlapTTest, Correl2OverlapTest and Corr2OverlapTest support this case, using two different approaches.

In the second case, there is no variable in common. This case might be employed when one pair represents one moment in time and the second pair represents the same subjects at another moment in time. The new array functions Correl2NonOverlapTest and Correl2NonOverlapTest support this case.

Accuracy Improvements

As mentioned above, Excel’s T.DIST, F.DIST and CHISQ.DIST functions (as well as the related functions and their Excel 2007 equivalents) round down the degrees of freedom to next lower integer. This is not a problem for most tests, but can give inaccurate results for some tests, and is especially a problem when the degrees of freedom is less than one.

In order to address this issue, we have replaced T.DIST.2T, F.DIST.RT, CHISQ.DIST.RT, etc. by their Real Statistics equivalents, T_DIST_2T, F_DIST_RT, CHISQ_DIST_RT, etc. for a number of Real Statistic tests (e.g. two sample t test with unequal variance, Hotelling’s T-square test with unequal variance and the Wilk’s version of MANOVA).

If we have not done this for some other test, please send me a comment so that we can correct this in a future release.

Fisher Exact Test

By default, there are limits to the size of the contingency tables supported by the FISHERTEST and FISHER_TEST functions. These limits were set since these functions can take a very long time to run with larger tables and so you may inadvertently block Excel. The limits for these functions have now been revised as follows.

Contingency tables with degrees of freedom less than 9 are supported; tables with 9 or higher degrees of freedom are currently not supported. For each supported table, there is a limit to the total cell count, i.e. the sum of all values in the table, as follows.

  • 2 × 2 – no limit, 2 × 3 – 2,000, 2 × 4 – 1,250,  2 × 5 – 360
  • 2 × 6 – 175,  2 × 7 – 110, 2 × 8 – 75,  2 × 9 – 40
  • 3 × 3 – 320,  3 × 4 – 95, 3 × 5 – 30

If you want to exceed these limits, you can add a third argument to the FISHERTEST function which describes how much you want to increase the limit. E.g. if you want to use the Fisher exact test for a 3 × 3 contingency table in range A1:C3 the sum of whose cells is 350, then you can use the array formula =FISHERTEST(A1:C3,,1.1). The 1.1 specifies that you have increased the limit for a 3 × 3 contingency table from 320 to 320 × 1.1 = 352. Since 350 < 352, the function will run, although it will take longer.

Enhancement for other resource intensive functions

In addition to the Fisher exact test functions listed above, the following functions are resource intensive and are limited in terms of the size of the samples supported.

  • A default limit of n1 + n2 = 28 (sum of the two sample sizes) has been set for MANN_EXACT, Perm2Dist and Perm2Inv, MannDist and MannInv
  • A default limit of sample size n = 25 has been set for SRANK_EXACT, SRANKPair_EXACT, PermDist and PermInv 

In the same manner as described above for FISHERTEST, you can add an argument (i.e. the final argument) to any of the above functions to explicitly change these limits.

Bug Fixes

  • Fixed bug in the GG_Epsilon function which caused this function and the HF_Epsilon function to produce an error value
  • Fixed bug in F_DIST(x, df1, df2, cum) when cum = FALSE
  • Fixed the formatting for the Mixed Repeated Measures data analysis tool when the Standard formatting and Regression options were chosen. When more than a few independent variables were used, the analysis portion of the output tried to overwrite the descriptive statistics portion of the output. This has now been fixed.
  • Moved the heading of the output from the Three Factor ANOVA data analysis tool one cell to the right
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Release 5.0 for Mac

New Mac Release

Good news for Mac users. The latest release of the Real Statistics Resource Pack (Release 5.0) is now available for use with Excel 2016 for the Mac. You can now download this release at Real Statistics Resource Pack for Mac.

There is also a new release of the Real Statistics Resource Pack that is compatible with Excel 2011 (Mac), but this has not been tested. You can download this version from Real Statistics Resource Pack for Mac as well. I would appreciate your informing me whether this release works on your Mac computer.

I have put in considerable energy and investment to create this new release and test it on a Mac computer. Any donation from you would be appreciated to help offset my costs.

User Interface

The user interface for the Mac version of the Real Statistics data analysis tools is identical to the Windows version with one important difference. When inserting a range into an input field, in Windows you can simply highlight the range of cells and the field will automatically contain the address of the highlighted range (see Figure 1).

Insert range Windows

Figure 1 – Inserting a Range in Windows

In the Mac version of Real Statistics to accomplish the same thing, you need to click on the + button, as shown in Figure 2.

Insert range on Mac

Figure 2 – Inserting a Range on the Mac (step 1)

This will display the dialog box shown on the right side of Figure 3. You can now highlight the desired data range (M3:M7 in this example) and when you press the OK button, the Input Range field will automatically be filled with the appropriate cell range address.

Insert range dialog Mac

Figure 3 – Inserting a Range in the Mac (step 2)

The situation is the same for the Output Range, except that now you should only highlight one cell.

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Release 5.0

I am pleased to announce Release 5.0 of the Real Statistics Resource Pack. The new release is now available for free download at Download Resource Pack for Excel 2007, 2010, 2013 and 2016 (Windows version) environments.

I am still working on Release 5.0 for the Mac, and I expect this to be available in June.

The Examples Workbook Part 1 has now been split into two files: Examples Workbook Part 1A and Examples Workbook Part 1B. These files as well as Examples Workbook Part 2 have been updated for compatibility with Release 5.0. The reliability examples, except for the ICC examples, can now be found in Workbook Part 1B and not Workbook Part 2.

The Real Statistics website will be updated over the course of the next several days to reflect the new capabilities in Release 5.0.

My apologies to all of you who have been waiting for the Real Statistic book. The revised timeframe for Real Statistics using Excel – Fundamentals is now September 2017.

Also thanks to all of you who have given donations to help sustain the Real Statistics project. This is most appreciated as are the countless number of people who have identified errors and who have made suggestions to improve the software and website.

The following is a summary of the new features in Release 5.0.

Krippendorff’s Alpha

Support for Krippendorff’s Alpha, another approach to inter-rater reliability, has been added. This approach has the advantage that it supports categorical, ordinal, interval and ratio type data and also handles missing data.

New functions have been added (KALPHA, KTRANS, KRIP_SES, KRIP_SER, KRIP) to support Krippendorff’s Alpha as well as a new data analysis tool.

Gwet’s AC2

Support for Gwet’s AC2 has also been added.  Gwet’s AC2 is yet another approach to inter-rater reliability which is similar to Krippendorff’s Alpha

New functions have been added (GWET_AC2, GWET_SES, GWET_SER, GTRANS, GWET) to support Gwet’s AC2, as well as a new data analysis tool.

Reliability data analysis tools

The Reliability data analysis tool has been replaced by the following three data analysis tools:

  • Internal Consistency Reliability: Cronbach’s Alpha and Split Half / Guttman’s
  • Interrater Reliability: Cohen’s Kappa, Weighted Kappa, Kendall’s W, Bland-Altman, Intraclass Correlation, Krippendorff’s Alpha and Gwet’s AC2
  • Item Analysis: Discrimination Index, Difficulty Index, Point Biserial Correlation

Distribution Fitting Capabilities

The goal of these new capabilities is to determine how to fit various distributions to sample data. In particular, new functions have been added to estimate the parameters of these distributions using the method of moments (WEIBULL_FITM, GAMMA_FITM, BETA_FITM, UNIFORM_FITM), maximum likelihood (WEIBULL_FIT, GAMMA_FIT, BETA_FIT, UNIFORM_FIT) and regression (WEIBULL_FITR).

Anderson-Darling Test

The Anderson-Darling Test is a way of determining whether a specified distribution is a fit for a given sample. This test is now provided for the following distributions: normal, exponential, Weibull, gamma and generic (i.e. any distribution with no unknown parameters).

New functions have been added (ANDERSON, ADTEST, ADCRIT, ADPROB) to support the Anderson-Darling Test, as well as a new data analysis tool.

Chi-square Goodness of Fit Test

New distribution-specific capabilities have been added to complement the existing FIT_TEST function. The following distributions are initially supported: normal, exponential, Weibull, gamma, beta and uniform. The new GOFTESTExact function can be used when the distribution parameters are known and the new GOFTEST function can be used when the distribution parameters are not known. In addition these tests can be performed via a new data analysis tool.

Non-parametric data analysis tools

The Non-parametric data analysis tool has been split into the following two data analysis tools:

  • Non-parametric Tests: Friedman’s Test, Runs Tests, Cochran’s Q Test, Moods’ Test
  • Goodness of Fit Tests: Two Sample Kolmogorov-Smirnov Test, One Sample Anderson-Darling Test, Chi-square Goodness of Fit Test

Changes to the User Interface

Upon pressing Ctrl-m (or an equivalent) you have access to the various data analysis tools via the original interface or the newer MultiPage interface. A new Corr tab has been added to the MultiPage interface that provides access to the following data analysis tools: Correlation Tests, Polychoric Correlation as well as the three reliability data analysis tools described above.

A new Reliability option has been added to the original interface, which gives access to the three reliability data analysis tools described above. Also a Goodness of Fit option has been added.

Improved Box Plots

The existing Box Plot and Box Plot with Outliers data analysis capabilities have been revised to better handle negative data elements. In such cases, you should refer to the labels for the y axis shown on the right side of the chart. Big thanks to Bob who explained how to make this improvement!

In addition, the Box Plot now shows the mean for each group (via an × on the chart)

Statistical Tables

A Two Sample Kolmogorov-Smirnov table of critical values has been added as well as One Sample Anderson-Darling tables of critical values.

The One Sample Kolmogorov-Smirnov table of critical values has also been revised. This also improves the accuracy of the KSCRIT and KSPROB functions. Errors in the KSCRIT, KSPROB and KINV functions have also been fixed.

Two Sample Kolmogorov-Smirnov Test

A new KS2CRIT function has been added which automatically performs the lookup of values in the Two Sample Kolmogorov-Smirnov table of critical values. In addition, the new KS2PROB function estimates the p-value for the Two Sample KS test based on interpolation between values in the Two Sample Kolmogorov-Smirnov table of critical values.

Polygamma Function

The POLYGAMMA worksheet function has been added to calculate the digamma and trigamma functions.

Bug Fixes

  • Fixed the LCRIT and LPROB functions for n > 50
  • Fixed the LogitSelect function, which did not work properly
  • Fixed the Three Factor ANOVA using Regression (totals were not calculated)
  • Fixed the VAR_POWER function (roles of the two parameters were reversed)
  • Fixed Chi-square Independence Test data analysis tool when the standard format was used without headings
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Release 4.14

I am pleased to announce Release 4.14 of the Real Statistics Resource Pack. The new release is now available for free download at Download Resource Pack for Excel 2007, 2010, 2013 and 2016 (Windows version) environments.

Note that now there are three versions of the software: one for Excel 2013/2016, another for Excel 2010 and a third for Excel 2007.

A new version for the Mac will be available within the next few weeks.

The Examples Workbook Parts 1 and 2 and the Multivariate Examples files have been updated for compatibility with the new release.

The Real Statistics website will be updated over the course of the next few days to reflect the new capabilities in Release 4.14.

Discriminant Analysis

A new Discriminant Analysis data analysis tool has been added to the multivariate analysis part of the Real Statistics Resource Pack. The tool will perform both linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA).

Classification tables and predictions for training and non-training data can be made.

Polychoric Correlation

A new Polychoric Correlation data analysis tool has been added which calculates the polychoric correlation for two discrete, finite, ordinal variables (using Solver). Data for such variables can be organized into a two dimensional contingency table (as for the chi-square test of independence). When the two variables are dichotomous, the polychoric correlation is called a tetrachoric correlation.

In addition, the TCORREL function has been added which estimates the tetrachoric correlation coefficient, along with a p-value and confidence interval

Percentile and Quartile Functions

New QUARTILE_EXC(R1, k) and PERCENTILE_EXC(R1, p) functions have been added which have the same functionality as QUARTILE.EXC and PERCENTILE.EXC. This is useful for Excel 2007 users since this version of Excel doesn’t support the .EXC functions. These functions do differ from their Excel counterparts only in the extreme cases: where the Excel function return #NUM!, the Real Statistics functions return MIN(R1) and MAX(R1).

In addition, these functions take a final argument which provides other options for defining percentile and quartile based on Hyndman-Fan methods 4, 5, 6, 7, 8 and 9 (note that Excel’s .EXC approach is method 6 and .INC is method 7). QUARTILE_EXC(R1, k, m) and PERCENTILE_EXC(R1, p, m) default to method 6 when m is omitted.

Fisher test effect size

The FISHER_TEST function has been added, which not only reports the p-value for the Fisher exact test (as is done by FISHERTEST), but also estimates equivalent phi and Cramer V effect sizes.

Bug Fixes

  • Fixes bug in Cluster Analysis data analysis tool when writing to another webpage
  • Fixes bug in SVD functions
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