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Course Material

Week 1: Objective of statistical analysis and theory with respect to inferential statistics
Week 2: Criteria for the choice of families of models, the likelihood, sufficient statistics, some general principals of statistics inference
Week 3: Point estimation: General considerations on bias and variance
Week 4: Maximum likelihood estimation and Cramer–Rao inequality
Week 5: Sufficient Statistics and Exponential family and Methods of Evaluating the estimators
Week 6: Interval estimation, Confidence interval of parameters for normal and non-normal distributions
Week 7 : Robustness and robust measures of location and scale
Week 8: Measuring the robustness by sensitivity analysis and breakdown point
Week 9: MLEs and their properties
Week 10: Hypothesis testing, basic concepts and applications
Week 11: Simple Likelihood Ratio Tests, MPT and UMPT
Week 12: Generalized Likelihood Ratio Tests
Week 13: GLRT for Two Sample Problems
Week 14: Asymptotic theory: Wilks Theorm and its applications
Week 15: Robust Inference
Week 16: Distribution Free tests

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