Course objective: Introducing basic statistical methods for testing the existence of an effect at a population level using data collected on a representative sample.

Organization: The course is divided into five sessions. Each session is made of a lecture and (at least) two practical classes. In those in-class practical classes, students are given the opportunity to tackle problem-solving exercises, with or without the use of R.

The following documents are provided for each session:

2021-2022: all in-class activities (practical sessions) here.

2021 examination: exam

Assignments: see instructions here.

Session 1

Objective: Introducing the principles of statistical inference and especially hypothesis testing. What does the question “Is there an effect of this on that?” mean in practice?

Session 2

Objective: Introducing the F-test for the group mean comparison.

Session 3

Objective: Introducing the t-test for the two-group mean comparison, the power of a t-test, the Bonferroni correction for the multiplicity of simultaneous tests.

Session 4

Objective: Introducing the paired t-test for the two-group mean comparison and the simple linear regression model.

Session 5

Objective: Introducing the F-test in the simple linear regression model and the prediction issue. The lecture ends with the implementation of an F-test to conclude about group differences between linear effects (an example of interaction effect).