XLSTAT version 2021.4

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Our new version is now available. What’s new? 

  • MyAssistant, a new learning tool

We’ve developed for you a new, dynamic interface that will easily and quickly help you to master XLSTAT. Check out our video and find out more. 

 

What is LASSO regression?

LASSO regression allows you to overcome the shortcomings (instability of the estimate and unreliability of the prediction) of linear regression in a high dimensional context.

Therefore, we can make predictions when our data set is composed of a very large number of variables compared to the number of individuals.

 

When can we use it?

A simple example: we can try to predict the composition of different water cookies from 35 explanatory variables, corresponding to the discretizations of near infrared spectra.

Ready to discover LASSO regression? Download our dataset and run your first analysis!

 

What's new in XLSTAT?

Following the numerous requests received by our users, we have added the LASSO regression to the XLSTAT modeling menu!

With the Lasso regression feature, you can now select your dependent variables and your explanatory variables in just a few clicks, thanks to its user-friendly dialog box. Among the available outputs, you will be able to visualize the table of predictions and residuals for all the observations, as well as the associated graphs and the evolution of the MCE (Mean Square Error).

 

Access this new feature under the Modeling data menu.

 

 

What is logistic regression?

Logistic regression allows you to study the relationship between a qualitative response variable and a set of qualitative and/or quantitative explanatory variables. More specifically, it helps you explain the occurrence or non-occurrence of an event (the dependent variable noted Y) by the level of explanatory variables (noted X).

 

When can we use it?

A simple example: Given a sample of customers, logistic regression will help us predict whether a customer will renew his subscription or not to an online reading service according to certain characteristics (age range, number of pages read last week, etc.).

Ready to discover logistic regression? Download our dataset and run your first analysis!

 

For Logistic Regression, what's new in XLSTAT?

XLSTAT allows you to model a binary (2 modalities), ordinal (more than two ordered modalities) or multinomial (more than two modalities) qualitative variable according to quantitative or qualitative explanatory variables.

Here are the enhancements of logistic regression in this new version:

  • a more ergonomic dialog box,

  • improvement of the computation time,

  • addition of the classification table to display the percentage of well classified observations,

  • the confusion plot to better visualize the classification table,

  • the GCI index, developed by our very own R&D team, to evaluate the predictive quality of your classification model - this is super useful!

Access this new feature under the Modeling data menu.

 

  • MANOVA (available in all XLSTAT solutions)

 

What is MANOVA analysis?

Multivariate analysis of variance allows you to study the relationships between several quantitative variables to be explained via a set of qualitative and/or quantitative explanatory variables.

The advantage of using a MANOVA instead of several simultaneous ANOVAs is that it takes into account the correlation between the response variables and thus allows better use of the information from the data.

 

When can we use it?

A simple example: using MANOVA we can find out whether three flower species differ in morphology, a variable represented by the combination of 4 characteristics (sepal length, sepal width, petal length and petal width).

Ready to discover a MANOVA analysis? Download our dataset and run your first analysis!

 

For MANOVA, what's new in XLSTAT?

In this new version, the interface of the MANOVA dialog box has been reorganized to be in line with the XLSTAT philosophy; keeping things simple, intuitive and where you’d expect them to be. In addition, this function is now more efficient for large datasets.

With this feature you can display the results of the Wilks, Hotelling-Lawley, Pillai and Roy tests as well as the graph of the means.

Access this new feature under the Modeling data menu.

 

 

How to get XLSTAT 2021.4?

Version 2021.4 will give you access to all the above improvements, advanced options and increase the performance of your software. Installing our new version is recommended for all users.

If you are currently using our trial version or have a valid license, you can download version 2021.4 for free at:

 

If you have a perpetual license without access to free upgrades and maintenance, please or contact us for further information.


Letzte Veranstaltungen

This module focuses on Analysis of Variance, but this technique makes assumptions about the underlying distributions in our data

This course covers the excellent features in XLSTAT for investigating, visualising and modelling data sets with measurements on many variables.

This short course delivered online will show consumer scientists how to set up and learn about the routines available in XLSTAT for relating consumer acceptability to sensory/analytic measures.

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