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.

## 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

No

## 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

 Mo Tu We Th Fr 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