9. Glossary

Principal component analysis (PCA)

Principal component analysis (PCA) is a method of statistical data analysis that reduces the number of initial variables by retaining only the main components or axes. Reduction to these independent axes enables data variability to be better explained and interpreted.

ANOVA

ANOVA is a statistical approach that highlights the variance observed in a variable as a function of other so-called explanatory variables. It is referred to as a one-factor or multifactor analysis, depending on the number of variability factors.

Emotional descriptor

Emotional descriptors are adjectives that characterize the consumer's reaction to a product-service stimulus. This reaction is situated on three axes of intensity (strong,...