XLSTAT New Version: You help make XLSTAT better for everyone

A new version of XLSTAT is available! Update your XLSTAT now to benefit from new features and new outputs.

What's new?

Our new XLSTAT version gives you access to the new Friedman-Rafsky feature as well as several improvements to the ANOVA and similarity/dissimilarity matrix features.

Friedman-Rafsky test

The Friedman-Rafsky test has been added to our list of non-parametric tests. It allows to compare the distributions of two samples of quantitative data when they are described by more than one attribute/variable.

The interface gives you the choice between 4 different distances (Canberra, Chebychev, Euclidienne and Manhattan) and 3 algorithms to find the minimum spanning tree according to your data set (Chazelle using Soft-Heap, Kruskal and Boruvka).

An easy example: you know the weight and height of a Basketball team and a Football team. Use this test to determine if these two samples (teams) follow the same distribution. Click here to learn more.

This feature is available in all XLSTAT solutions (except Basic)

Similarity/Dissimilarity Matrices

This feature allows you to calculate the similarities or dissimilarities between your observations or variables. XLSTAT offers many proximity measures to which we have added, in the context of binary data, two popular indices in supervised and unsupervised classification: the Rand and Adjusted Rand indices. These indices can be used to build a matrix before running a classification.

Moreover, it is now possible to enter large-volume data thanks to the file importation mode in XLSTAT.

Click here to access our tutorial.

This feature is available in all XLSTAT solutions

ANOVA

Several improvements have been added to our ANOVA functionality.

Improvement 1: Addition of groups

It is now possible to select a group variable in the General tab when your observations are associated with a group. This can be very helpful if your data is split into many sub-samples and you want to run an ANOVA for each subsample simultaneously.

Improvement 2: Add effect size measures

P-values tend to decrease when the sample size is increased. This may lead to falsely significant results in the case of large samples and thus to “wrong” interpretations.

For this reason, we have added effect size measures. They do not dependent on the sample size and allow better conclusions.

Improvement 3: Adding stars to the p-values

In order to quickly visualize the significance levels of the p-values, we have added stars to the ANOVA result tables.

Improvement 4: Sorting in the means charts

For an easier comparison of means, we have added an option in the Means sub-tab that allows you to sort means in descending order.

This feature is available in all XLSTAT solutions

How to install this update?

This new version will give you access to all the new features mentioned above. Installation of our new version is recommended for all users.

If you are currently using our trial version or if you have an active XLSTAT 2022.4 license, you can download the new version for free here.