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Stat 135

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Lectures
Lecture 1: Syllabus & Diagnostic Test
Lecture 2: Survey Sampling, Introduction
Lecture 3: Survey Sampling, Inference
Lecture 4: Wrapping up Sampling
Lecture 5: Method of Moments
Lecture 6: MoM & Mathematical Digressions
Lecture 7: Standard Errors of MoM Estimators
Lecture 8: Computing Standard Errors, continued
Lecture 9: The Bootstrap; and Introducing Maximum Likelihood Estimation
Lecture 10: Maximum Likelihood Estimation
Lecture 11: MLE and the Multinomial Distribution
Lecture 12: Mean Squared Error and Consistency
Lecture 13: Consistency of the Maximum Likelihood Estimator
Lecture 14: Asymptotic Distribution of the Maximum Likelihood Estimator
Lecture 15: Proof of Asymptotic Normality, and Confidence Intervals
Lecture 16: Efficiency
Lecture 17: Proof of the Cramér-Rao Lower Bound
Lecture 18: Sufficiency, and the Factorization Theorem
Lecture 19: Proof of the Factorization theorem and the Rao-Blackwell Theorem
Lecture 20: Proof of the Rao-Blackwell Theorem and Properties of Estimators
Lecture 21: Introducing Hypotheses Tests
Lecture 22: Testing Hypotheses: Vocabulary and Examples
Lecture 29: Generalized Likelihood Ratio Test for the Multinomial Model
Lecture 30: Hypothesis Tests for Categorical Data
Lecture 31: Fisher’s Exact Test
Lecture 32: The Chi-square Test for Homogeneity
Lecture 33: The Chi-square Test for Independence
Lecture 34: Matched-Pair Designs
Lecture 35: Two sample tests: The t-test
Lecture 36: Power Computations
Lecture 37: Two sample tests: Nonparametric Tests
Lecture 38: Two sample tests: Nonparametric Tests, part 2
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Course Calendar

Here is the calendar of events for Stat 135, Spring 2026.