MAT 242 - Statistics

Course Objectives

This course is designed to provide the student with a solid background and understanding of the basic results and methods in mathematical statistics and related subjects.
Explain the meaning of statistical models, hypothesis testing and its main principles.

Course Description

Statistical models. Main principles and theories of hypothesis testing. Parameter estimation, the likelihood function and maximum likelihood estimators. Properties of estimators: unbiased estimators; consistent estimators, Fisher information and efficient estimators, Asymptotic properties of MLE. Confidence interval and tests, Optimal tests: randomized test; powerful test, Neyman-Pearson theorem, Uniformly most powerful test; likelihood ratio test; Sufficient statistics: definition of sufficiency, The Factorization and Fisher-Neyman criteria.Midterm, The Rao-Blackwell theorem. Minimal and complete sufficient statistics, Best unbiased estimators and the Lehmann-Scheffe theorem.Some One-sample, Two-sample and Paired models. One-way and Two-way Anova. Regression analysisRegression analysis.