Statistical Inference Training

Week 1: Revision of Probability, Different Discrete and Continuous Distributions
Week 2: Functions of Random Variables and their distributions, T, Chi-sq, F distributions and their Moments
Week 3: Introduction of statistics and the distinction between Data and its properties, and probabilistic models
Week 4: Estimator and methods of estimation, Properties of an estimator: Consistency, Unbiasedness, Efficiency and Sufficiency
Week 5: Neyman Factorization, Cramer-Rao Bound
Week 6: Confidence Intervals, Concepts of hypothesis testing, Characteristics of Good Hypothesis, null and Alternative Hypotheses, Types of Errors
Week 7: Inference on Population mean, Comparing two population means, Inference on Variance, Comparing two population variance
Week 8: Neyman Pearson Lemma