# Lecture Notes

 01 Probability Theory, Probability Space, Random Variables, Cumulative Distribution Function(section-by-section | single page)
 10 Finding UMVU Estimators, Complete Statistics, Cramér-Rao Lower Bound(section-by-section | single page)
 02 Random Variables, Leibniz Rule and Transformations of RVs(section-by-section | single page)
 11 Hypothesis Testing, Power Function, Selecting the Critical Value(section-by-section | single page)
 03 Expectations of RVs and Moments(section-by-section | single page)
 12 Hypothesis Testing (cont.), LRT, LM, Wald, Test Equivalence, Test Optimality(section-by-section | single page)
 04 Examples of Distributions(section-by-section | single page)
 13 Test Optimality (cont.), 2-sided tests, p-values, Interval Estimation(section-by-section | single page)
 05 Families of Distributions, Chebychev's Inequality, Multiple Random Variables(section-by-section | single page)
 14 Convergence, Law of Large Numbers, Central Limit Theorem, Delta Method(section-by-section | single page)
 06 Multiple RVs (cont.), Conditional Moments, LIE, CVI, Covariance and Correlation, Some Inequalities(section-by-section | single page)
 15 Asymptotic Properties of ML Estimators(section-by-section | single page)
 07 Random Sample, Statistics, Statistical Inference(section-by-section | single page)
 16 Bayesian Estimation(section-by-section | single page)
 08 Point Estimation, Method of Moments, Maximum Likelihood(section-by-section | single page)
 17 OLS, Normal Linear Model, Asymptotic Properties(section-by-section | single page)
 09 Point Estimation (cont.), Evaluating Estimators, UMVU, Sufficient Statistics, Rao-Blackwell(section-by-section | single page)
 18 Multicollinearity, Partitioned Regression, Gauss-Markov Theorem(section-by-section | single page)