MATH-341 / 5 credits

Teacher: Panaretos Victor

Language: English


Summary

Regression modelling is a basic tool of statistics, because it describes how a random variable of interest may depend on other variables. The aim of this course is to familiarize students with the basis of regression modelling, and of some related topics.

Content

Learning Prerequisites

Recommended courses

Analysis, Linear Algebra, Probability, Statistics

Learning Outcomes

By the end of the course, the student must be able to:

  • Recognize when a linear model is appropriate to model dependence
  • Interpret model parameters both geometrically and in applied contexts
  • Estimate the parameters determining a linear model from empirical observations
  • Test hypotheses related to the structural characteristics of a linear model
  • Construct confidence bounds for model parameters and model predictions
  • Analyze variation into model components and error components
  • Contrast competing linear models in terms of fit and parsimony
  • Construct linear models to balance bias, variance and interpretability
  • Assess / Evaluate the fit of a linear model to data and the validity of its assumptions.
  • Prove basic results related to the statistical theory of linear models

Teaching methods

Lectures ex cathedra, exercises in class, take-home projects

Assessment methods

Continuous control, final exam.

Seconde tentative : Dans le cas de l'art. 3 al. 5 du Règlement de section, l'enseignant décide de la forme de l'examen qu'il communique aux étudiants concernés.

Supervision

Office hours No
Assistants Yes
Forum Yes

In the programs

  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Linear models
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Linear models
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Linear models
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Linear models
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks
  • Semester: Fall
  • Exam form: Written (winter session)
  • Subject examined: Linear models
  • Lecture: 2 Hour(s) per week x 14 weeks
  • Exercises: 2 Hour(s) per week x 14 weeks

Reference week

 MoTuWeThFr
8-9    MAA330
9-10    
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17  MAB111  
17-18    
18-19     
19-20     
20-21     
21-22     

Wednesday, 16h - 18h: Lecture MAB111

Friday, 8h - 10h: Exercise, TP MAA330