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The Reliability data analysis tool has been replaced by the following three data analysis tools: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
This entry was posted in Announcement, New Release. Bookmark the permalink.

Leave a Reply

Your email address will not be published. Required fields are marked *