Statistical Inference


Lecture 1 - Introduction and Motivation


Lecture 2 - Basic Concepts of Point Estimations - I


Lecture 3 - Basic Concepts of Point Estimations - II


Lecture 4 - Finding Estimators - I


Lecture 5 - Finding Estimators - II


Lecture 6 - Finding Estimators - III


Lecture 7 - Properties of MLEs


Lecture 8 - Lower Bounds for Variance - I


Lecture 9 - Lower Bounds for Variance - II


Lecture 10 - Lower Bounds for Variance - III


Lecture 11 - Lower Bounds for Variance - IV


Lecture 12 - Sufficiency


Lecture 13 - Sufficiency and Information


Lecture 14 - Minimal Sufficiency, Completeness


Lecture 15 - UMVU Estimation, Ancillarity


Lecture 16 - Invariance - I


Lecture 17 - Invariance - II


Lecture 18 - Bayes and Minimax Estimation - I


Lecture 19 - Bayes and Minimax Estimation - II


Lecture 20 - Bayes and Minimax Estimation - III


Lecture 21 - Testing of Hypotheses : Basic Concepts


Lecture 22 - Neyman Pearson Fundamental Lemma


Lecture 23 - Applications of NP lemma


Lecture 24 - UMP Tests


Lecture 25 - UMP Tests (Continued.)


Lecture 26 - UMP Unbiased Tests


Lecture 27 - UMP Unbiased Tests (Continued.)


Lecture 28 - UMP Unbiased Tests : Applications


Lecture 29 - Unbiased Tests for Normal Populations


Lecture 30 - Unbiased Tests for Normal Populations (Continued.)


Lecture 31 - Likelihood Ratio Tests - I


Lecture 32 - Likelihood Ratio Tests - II


Lecture 33 - Likelihood Ratio Tests - III


Lecture 34 - Likelihood Ratio Tests - IV


Lecture 35 - Invariant Tests


Lecture 36 - Test for Goodness of Fit


Lecture 37 - Sequential Procedure


Lecture 38 - Sequential Procedure (Continued.)


Lecture 39 - Confidence Intervals


Lecture 40 - Confidence Intervals (Continued.)