Statistical Inference Practice



Vincent Vandewalle,

Kevin Mottin,

Content and organization

In this course we will develop statistical inference from the practical point of view. We will first make a brief introduction on point estimation and confidence sets. Then we will focus on non-parametric inference (empirical pdf, plug-in estimators). In a third section we will introduce bootstrapping which permits to get confidence intervals by resampling in the data. In a fourth section we will study method of moments and maximum likelihood inference from a practical point of view. In a firth section we will work on multiple regression from a practical point of view.

Course 1 : Introduction to statistical inference and learning

Course 2 : Empirical study of some estimators by computation and simulations

Course 3 : Non-parametric inference

Course 4 : Exercises on non-parametric inference

Course 5 : Bootstrap

Course 6 : Exercises on bootsrap

Course 7 : Method of moments and maximum likelihood

Course 8 : Exercises of method of moments and maximum likelihood

Course 9 : Multiple linear regression

Course 10 : Exercises on multiple linear regression



Course Duration

30 h

Course Type

Semester Course


Monday from 9h to 12h



Modality (online/in person):


Host Institution
Université Côte d'Azur

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