Interested in joining our September 2023 batch? Applications opens on 14th June 2023.

Interested in joining our September 2023 batch? Applications opens on 14th June 2023.

Degree Level Course

Linear Statistical Models

To introduce linear statistical models and their applications in estimation and testing. The course will illustrate concepts with specific examples, data sets and numerical exercises using statistical package R.

by Siva Athreya

Course ID: BSCMA2001

Course Credits: 4

Course Type: Elective

Pre-requisites: None

Course structure & Assessments

For details of standard course structure and assessments, visit Academics page.

WEEK 1 Review of Estimation, Hypothesis Testing
WEEK 2 Review of working with R-package
WEEK 3 Least square estimation, estimable linear functions
WEEK 4 Normal equations
WEEK 5 Best Linear Unbiased Estimates (BLUEs).
WEEK 6 Gauss-Markov Theorem.
WEEK 7 Degrees of freedom. Fundamental Theorems of Least Square.
WEEK 8 Testing of linear hypotheses.
WEEK 9 One-way and two-way classification models
WEEK 10 ANOVA and ANCOVA.
WEEK 11 Nested models. Multiple comparisons
WEEK 12 Introduction to random effect models.
+ Show all weeks

Prescribed Books

The following are the suggested books for the course:

Plane Answers to Complex Questions The Theory of Linear Models, Springer by R. Christensen.

Linear Statistical Inference by C. R. Rao.

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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