5.00 credits
22.5 h + 22.5 h
Q1
Teacher(s)
Pircalabelu Eugen;
Language
French
Main themes
The course will focus on presenting key probabilistic / inferential concepts, to help students level up for more advanced courses.
Learning outcomes
At the end of this learning unit, the student is able to : | |
use the appropriate probabilistic model and determine quantities of interest based on it. | |
understand the properties of different probability distributions and use the "iid" (independent and identically distributed) framework to construct statistical estimators for unknown quantities of the population. | |
assess the quality of such estimators and supplement them with inference tools such as confidence intervals. | |
perform hypothesis testing and understand statistical errors associated with statistical decisions. | |
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.
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.
Faculty or entity
LSBA