Course Page - IIT Madras Degree Program

Degree Level Course

Linear Models with Applications

by Siva Athreya

Course ID: BSMA3015

Course Credits: 4

Course Type: Elective

Pre-requisites: None

Course structure & Assessments

12 weeks of coursework, weekly online assignments, 2 in-person invigilated quizzes, 1 in-person invigilated end term exam. For details of standard course structure and assessments, visit Academics page. For details of standard course structure and assessments, visit Academics page.

WEEK 1	Review of Estimation, Hypothesis Testing, Review of working with R-package, Guided Project Information handout
WEEK 2	Fundamentals of Linear Model, Least square estimation, Estimable linear functions
WEEK 3	Normal equations, Indicator variables and Interaction terms, Best Linear Unbiased Estimates (BLUEs), Gauss-Markov Theorem
WEEK 4	Model Adequacy Checks, Residual Analysis, Influence and Leverage Points, Residual Plots
WEEK 5	Transformations to Linearize the Model, Variance – Stabilizing Transformations, Box – Cox Transformation, Generalized and Weighted Least Squares, Guided Project Discuss
WEEK 6	Logistic regression, GLMs for general Exponential Family, GLM Log-likelihood, Gradient, and Hessian
WEEK 7	Distribution of MLE, Prediction and estimation, Guided Project Description and Selection
WEEK 8	Testing of linear hypotheses, Model Selection, AIC and BIC
WEEK 9 - Week 12	Guided Project execution and report writing

+ Show all weeks

About the Instructors

Siva Athreya

Professor, International Centre for Theoretical Sciences - TIFR and Indian Statistical Institute, Bangalore Centre

Siva Athreya received his Bachelor of Science (Honours) Mathematics from St. Stephen’s College, New Delhi, India in 1991. After obtaining a Master of Statistics from Indian Statistical Institute, Kolkata, India in 1993 he obtained his PhD in Mathematics from the University of Washington, Seattle, U.S.A. in 1998. His research interests include: Stochastic Analysis (Stochastic Partial Differential Equations and Stochastic Differential Equations); Random walks among mobile traps; Random Graphs; Tree-valued Processes; Computational Epidemiology. He currently serves as Editor-in-Chief: Electronic Communications in Probability.

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