Quantile regression for the evaluation of student satisfaction

Cristina Davino, Domenico Vistocco
(2008) Statistica Applicata - Italian Journal of Applied Statistics, Vol. 20, Number 3, 179-196, ISSN 1125-1964


This paper aims to analyse the internal effectiveness of a University educational process through quantile regression. Such approach allows to take into account the effect the main features of a course play on student satisfaction. As a matter of fact quantile regression allows to focus on the effects that the explanatory variables have on the entire conditional distribution of the dependent variable and it is then able to catch the different effect of course features for unsatisfied and very satisfied students. Moreover, the quantile regression estimates are used to detect typologies either exploiting a stratification variable or using similarities in the dependence model.