Very useful in geosciences.

MDS is a form of a PCA- often used in sensory science. The MDS uses the input of a similarity/dissimilarity matrix to obtain a 2-D visualization of the similarities and differences between products/subjects based on their proximity to one another ...

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) ...

Hi, I have a question regarding the modeling data section. I have an XLSTAT-Premium version to deal with the metabolomics data. PCA and PLS-DA contributed a lot to explore my dataset. However, nowadays Orthogonal Partial least squares discriminant...

The quality of an ANCOVA depends on the heteroscedasticity and the normality of residuals. Currently, these two aspects are not part of the output of the ANCOVA analysis. They have to be manually calculated (in the basic version for normality, i...

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).

In the {Significance by cell (Fisher's exact test)} table, we can only get < or >.It would be valuable to have the corresponding p-values per cell.

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...

It is useful in terms of crossvalidating the results and is implemented in other software