Math 2.0

Resources / course

Statistical Inference JYMXY87FXT

URIm2://res/JYMXY87FXT
Kindcourse
CreatorsSomesh Kumar (instructor)
Date2013-06-11
Scopein
Idscourse 03w5sq511:111105043, course 03w5sq511:111105124

Expressions

e1: edition

Languageen
Date2013-06-11
Contents
  • part 1: Introduction and Motivation
  • session 1: Introduction and Motivation
  • part 2: Basic Concepts of Point Estimations - I
  • session 2: Basic Concepts of Point Estimations - I
  • part 3: Basic Concepts of Point Estimations - II
  • session 3: Basic Concepts of Point Estimations - II
  • part 4: Finding Estimators - I
  • session 4: Finding Estimators - I
  • part 5: Finding Estimators - II
  • session 5: Finding Estimators - II
  • part 6: Finding Estimators - III
  • session 6: Finding Estimators - III
  • part 7: Properties of MLEs
  • session 7: Properties of MLEs
  • part 8: Lower Bounds for Variance - I
  • session 8: Lower Bounds for Variance - I
  • part 9: Lower Bounds for Variance - II
  • session 9: Lower Bounds for Variance - II
  • part 10: Lower Bounds for Variance - III
  • session 10: Lower Bounds for Variance - III
  • part 11: Lower Bounds for Variance - IV
  • session 11: Lower Bounds for Variance - IV
  • part 12: Sufficiency
  • session 12: Sufficiency
  • part 13: Sufficiency and Information
  • session 13: Sufficiency and Information
  • part 14: Minimal Sufficiency, Completeness
  • session 14: Minimal Sufficiency, Completeness
  • part 15: UMVU Estimation,Ancillarity
  • session 15: UMVU Estimation, Ancillarity
  • part 16: Invariance - I
  • session 16: Invariance - I
  • part 17: Invariance - II
  • session 17: Invariance - II
  • part 18: Bayes and Minimax Estimation - I
  • session 18: Bayes and Minimax Estimation - I
  • part 19: Bayes and Minimax Estimation - II
  • session 19: Bayes and Minimax Estimation - II
  • part 20: Bayes and Minimax Estimation - III
  • session 20: Bayes and Minimax Estimation - III
  • part 21: Testing of Hypotheses :Basic Concepts
  • session 21: Testing of Hypotheses : Basic Concepts
  • part 22: Neyman Pearson Fundamental Lemma
  • session 22: Neyman Pearson Fundamental Lemma
  • part 23: Applications of NP Lemma
  • session 23: Applications of NP lemma
  • part 24: UMP Tests
  • session 24: UMP Tests
  • part 25: UMP Tests (Contd.)
  • session 25: UMP Tests (Contd.)
  • part 26: UMP Unbiased Tests
  • session 26: UMP Unbiased Tests
  • part 27: UMP Unbiased Tests (Contd.)
  • session 27: UMP Unbiased Tests (Contd.)
  • part 28: UMP Unbiased Tests : Applications
  • session 28: UMP Unbiased Tests : Applications
  • part 29: Unbiased Tests for Normal Populations
  • session 29: Unbiased Tests for Normal Populations
  • part 30: Unbiased Tests for Normal Populations (Contd.)
  • session 30: Unbiased Tests for Normal Populations (Contd.)
  • part 31: Likelihood Ratio Tests - I
  • session 31: Likelihood Ratio Tests - I
  • part 32: Likelihood Ratio Tests - II
  • session 32: Likelihood Ratio Tests - II
  • part 33: Likelihood Ratio Tests - III
  • session 33: Likelihood Ratio Tests - III
  • part 34: Likelihood Ratio Tests - IV
  • session 34: Likelihood Ratio Tests - IV
  • part 35: Invariant Tests
  • session 35: Invariant Tests
  • part 36: Test for Goodness of Fit
  • session 36: Test for Goodness of Fit
  • part 37: Sequential Procedure
  • session 37: Sequential Procedure
  • part 38: Sequential Procedure (Contd.)
  • session 38: Sequential Procedure (Contd.)
  • part 39: Confidence Intervals
  • session 39: Confidence Intervals
  • part 40: Confidence Intervals (Contd.)
  • session 40: Confidence Intervals (Contd.)

Catalogue records