Dans ce logiciel ,j'ai pas trouvé la méthode calcule des indices statistiques (indice de laspayres,fisher)

When performing the Kruskal-Wallis analysis of variance on k samples, up until now, you can choose between Dunn, Conover-Iman and Steel-Dwass-Critchlow-Fligner with the addition of Bonferroni correction (for the first two mentioned, respectively) ...

In a linear hierarchy regression, it is important to know the change in R-squared to know if additional variables in a model increase the association with the predictor variables between the models (independent variables).

To predict the Overall Liking resulted from decreasing the percentages of Too Weak or Too Strong. This method would help clients in prioritizing sensory aspects to improve.

We do a lot of ranking. From the ranking study, we can calculate r-index. Also d prime can be calculated from r-index. I believe there is a package in R already exist. It would be good to add this to XLSTAT.

The Nash-Sutcliffe efficiency , Willmott's index and Model Performance Index (MPI) are suitable indices to add XLSTAT for assessing model performance.

I'm a very happy and satisfied customer using XLSTAT. I've recently upgraded to MS Office 365 and was hoping that you could guide me to an App, or the process by which I can continue to use my XLStat with the online of MS Excel.

I think XLSTAT provides partial least squares models but not general least squares. This would be very practical for time series analysis, for instance.

Estimating lagged prediction models from autocorrelated historical data is a common challenge in business and economics. The resulting multicollinearity causes the models to perform poorly. The Almon lag method is a clever way to deal with the mul...

Spatial Autocorrelation Indices (e.g Moran's I) are mainstream of spatial statistics that are worth being implemented in XLSTAT software. They are useful for ecological studies.