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Ready to discover a MANOVA analysis? Download our dataset and run your first analysis! For MANOVA, what's new in XLSTAT? When can we use it?Ī 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). 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. 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. MANOVA (available in all XLSTAT solutions) What is MANOVA analysis? the GCI index, developed by our very own R&D team, to evaluate the predictive quality of your classification model - this is super useful!Īccess this new feature under the Modeling data menu.the confusion plot to better visualize the classification table,.addition of the classification table to display the percentage of well classified observations,.Here are the enhancements of logistic regression in this new version: 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. Ready to discover logistic regression? Download our dataset and run your first analysis! For Logistic Regression, what's new in XLSTAT? When can we use it?Ī 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.). 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). Logistic regression allows you to study the relationship between a qualitative response variable and a set of qualitative and/or quantitative explanatory variables. Logistic regression (available in all XLSTAT solutions) What is logistic regression? 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).Īccess this new feature under the Modeling data 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.
Ready to discover LASSO regression? Download our dataset and run your first analysis! What's new in XLSTAT?įollowing the numerous requests received by our users, we have added the LASSO regression to the XLSTAT modeling menu! When can we use it?Ī 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. Therefore, we can make predictions when our data set is composed of a very large number of variables compared to the number of individuals. 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. LASSO regression (available in all XLSTAT solutions except Basic) What is LASSO regression? We’ve developed for you a new, dynamic interface that will easily and quickly help you to master XLSTAT. What’s new? MyAssistant, a new learning tool
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