Week 3: Point estimation: General considerations on bias and variance
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
- Chapters 16
- Department Statistics
- Teacher
Dr. Hafiz Zafar Nazir
