This course has two objectives: (i) introduce the basics of probability theory, including a study of the main concepts of discrete and continuous probability, as well as (ii) present the basic elements of inferential statistics : sampling distributions, punctual parametric estimation, confidence intervals, hypothesis tests, chi-square tests, etc. A final chapter of regression models will also be included.
This course aims to getting the student familiar with the statistical thinking. The first part of the course deals with probability theory. The second part will deal with statistical inference. It focuses on estimation, confidence intervals, hypothesis testing and regression.
The exam will be in two parts. The written part is entirely on the statistical content of the course and is composed of one or two theoretical questions (to check the understanding of the statistical concepts and to measure his capacity for synthesizing) and of exercises (to test the practical ability, the way the student tackles a problem or analyses data or interpret results). These exercises are similar to those seen during the semester with the assistant. The oral part is dedicated to the probability part of the course and checks the global understanding of this theory. Final grade will be the arithmetic average of written and oral grades (if both are larger or equal to 10/20, minimum of the two grades otherwise).
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Standard | 0 | 3 | ||
| Standard | 2 | 3 |