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302316 (v.1) Statistical Inference 301



 

Area:Department of Mathematics and Statistics
Contact Hours:4.0
Credits:25.0
Lecture:3 x 1 Hours Weekly
Tutorial:1 x 1 Hours Weekly
Prerequisite(s):302315 (v.2) Mathematical Statistics 202 or any previous version
Procedures and properties of estimators - Fisher information, Cramer-Rao bound, consistency, sufficiency and Rao-Blackwell theorem. Hypothesis testing - Neyman-Pearson Lemma likelihood ratio, power function and confidence sets. Bayesian inference and nexus with likelihood. Monte Carlo, Boot-Strap and resampling Methods. Review of matrix algebra-random vectors, mean vectors and covariance matrices. Multivariate normal and its associated distributions.

 

 

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