This course is an introduction to the methods of statistical inference used in human sciences. It aims at familiarising student with statistical modelling, data treatment and data interpretation, using descriptive statistics and inferential tools. It also provides the necessary basics in probability theory. The primary objective of the course is to give students analytical and operational skills, i.e. providing them tool to analyse data in a critical, coherent and rigourous way in order to answer the statistical problem at hand.
There are several objectives to the course: (i) cover classical methods in descriptive statistics and train student to have a critical analysis of the derived (numeric or graphical) output; (ii) introduce the basic notions in probability theory and develop the students' mathematical rigour; (iii) cover statistical inference tools.
An introduction to descriptive statistics and basic probability. An introduction to discrete random variables. An introduction to the Normal distribution. An introduction to linear regression.
The written exam will evaluate both theory and exercises. Weekly quizzes and the mock exam will be optionally taken into account.
All resources will be available on webcampus: exercises sessions, slides (with annotations), etc.
| Training | Study programme | Block | Credits | Mandatory |
|---|---|---|---|---|
| Standard | 0 | 5 | ||
| Standard | 0 | 5 | ||
| Standard | 0 | 5 | ||
| Standard | 1 | 5 | ||
| Standard | 1 | 5 | ||
| Standard | 3 | 5 |