400 Level

Academic Year: 2022/2023
Semester: Semester I

Academic Year: 2022/2023
Semester: Semester I
Elementary Theorems on Linear and Matrix Algebra, Partitioned Matrices, Nonnegative Matrices; Generalized Inverses of Matrix; Solutions of Linear Equations; Idempotent Matrices, Trace of Matrices; Derivatives of Quadratic Forms, Expectation of Matrix, Multivariate Normal Distribution, Distribution of Quadratic Forms; General Linear Model, Optimal Estimation and Hypothesis Testing Procedures for the General Linear Model, Applications to Regression Models. Application of Optimal Inference Procedures for the General Linear Model to Multifactor Analysis of Variance, Experimental Design Models, Analysis of Covariance, Split-Plot Models, Repeated Measures Models, Mixed Models,
Variance Component Models.
Prerequisites: ST 105, ST 203, ST 301Recommended Texts:
1. Linear Models, S. R. Searle (1971) - John Wiley.
2. Linear Models, Least Squares and Alternatives, C.R. Rao and H. Toutenburg - Springer
3. Theory and Application of the Linear Model, F. A. Graybill (1976) - Duxbury.
4. Linear Regression Analysis, G.A.F. Seber (1977) - John Wiley.

Further reading:
1. Text Book: https://leanpub.com/lm, and the relevant R codes: https://github.com/bcaffo/lm .
2. YouTube videos:

Tentative Course Evaluation
Quizzes and Assignments - 30%
End Semester Examination - 70%