Teacher(s)

Pircalabelu Eugen;

Language

French

Content

The class is focused on the presentation of key probabilistic concepts such as:

• Point estimation
• Confidence intervals
• Hypothesis testing
• Type I and II errors
• Applications to the case of normal population(s) 
• Applications to the case of proportions.

Teaching methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

The class consists of lectures (15h) and exercises sessions (15h).
Teaching language: French.

Evaluation methods

Due to the COVID-19 crisis, the information in this section is particularly likely to change.

Written exam of 3 hours, closed book with the possibility of using a formulaire and a pocket calculator.
The exam consist of theoretical questions and exercises to be solved and a list of tables will be provided.
A 'test dispensatoire' (non-compulsory) will be organized in the beginning of the class and an evaluation (compulsory) before the regular exam session will be organized at the end of the class. These two forms of evaluation have an equivalent complexity as the exam in the regular exam session and are organized in a similar fashion.  
To be allowed to take part in the examination the student has to submit 3 compulsory homeworks (short, 1-2 pages maximum per homework). The homeworks are not graded as they are not part of the evaluation.
Submission of less than 3 homework results in failure of the course!

Online resources

Moodle website of the class: LSTAT2013 - Concepts de base en statistique inférentielle.
https://moodleucl.uclouvain.be/course/view.php?id=12921

Bibliography

• Wackerly, D.D., Mendenhall, W. et Scheaffer, R.L. (2007). Mathematical Statistics with Applications, 7th Ed., International student edition, Brooks-Cole.
• Rice J.A. (2007). Mathematical Statistics and Data Analysis 3rd Ed., Duxbury Press.
• Droesbeke, J.-J. (1997). Eléments de Statistique. Editions de l’Université de Bruxelles & Editions Ellipses.
• Khuri, A (1993). Advanced calculus with applications in statistics, Wiley, New York.

Teaching materials

• Transparents du cours et syllabus disponible sur Moodle

Faculty or entity

LSBA