Linear Statistical Models

This is the webpage for the Linear Models course (B. Stat. (hons) III, 2020).

Notice board

Video lectures and exercises

Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Exercise set 1
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
Lecture 22
Lecture 23
Lecture 24: Multiple hypotheses testing (part 1):
Exercise set 2
Lecture 25: Multiple hypotheses testing (part 2)
Lecture 26: Model selection
Lecture 27: Multiple hypotheses testing (part 3): using R
Lecture 28: Covariance structures (part 1)
Lecture 29: Covariance structures (part 2)
Lecture 30: Covariance structures (part 3): Using R
Lecture 31: Influence diagnostics (part 1)
Some reference material from Belsley, Kuh and Welsch
Lecture 32: Influence diagnostics (part 2)
Lecture 33: Multicollinearity (part 1)
Lecture 34: Multicollinearity (part 2)
A short discussion about different formuations of ridge regression.
Lecture 35: Multicollinearity in R: Ridge regression
Lecture 36: Multicollinearity in R: Lasso and subset selection
Lecture 37: Linear mixed effects models (part 1)
Lecture 38: Linear mixed effects models (part 2)
Lecture 39: Linear mixed effects models (part 3) Here is the paper mentioned in the video.
Lecture 40: Mixed effects models in R (part 1)
Lecture 41: Mixed effects models in R (part 2)
Lecture 42: Linear mixed effects models (part 4)
Exercise set 4
Lecture 43: Generalized linear models (part 1)
Lecture 44: Generalized linear models (part 2)
Lecture 45: Generalized linear models (part 3): Using R

Course assessment

No midsem, Sem 70 marks. Two projects worth 10 marks each. Assignments worth 10 marks.

Reference

The main textbook is Linear models with R by Julian J. Faraway. It is written in a non-mathematical way with due emphasis on the statistical applications.

A more mathematical exposition (not recommended for this course) is available in the following two books:

Linear Models_ An Integrated Approach by Sreenivasa Rao Jammalamadaka, Debasis Sengupta
Plane answers to Complex Questions by Ronald Christensen

A rather fat book (about 1400 pages) that presents everything in great details is

Applied Linear Statistical Models by Kutner, Nachtsheim, Neter and Li.

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Table of contents

Linear Statistical Models

Video lectures and exercises

Course assessment

Reference

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