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Stat 210a
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Course introduction
Probability
Statistical models and estimation
Exponential Families
Sufficiency
Completeness, Ancillarity, and Basu’s Theorem
Unbiased Estimation
Bayes Estimation
Interpretations of Probability and Sources of Priors
Markov Chain Monte Carlo
The James-Stein Estimator
Minimax Estimation
Hypothesis Testing and the Neyman-Pearson Lemma
Testing with One Real Parameter
p-values, confidence regions, and (mis-)interpreting Tests
Testing with Nuisance Parameters
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Handwritten lecture notes
Course Materials
Handwritten notes
Handwritten notes
Handwritten lecture notes
Lecture 1: Induction
Lecture 2: Probability
Lecture 3: Estimation