*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:

- a 1h-video lecture: a R tutorial whose slides, data and R script are
provided;

- a PDF file containing a self-directed learning exercise;
- two PDF files with in-class exercises.

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).