STAT 111

Introduction to Statistical Inference

Section 1: Introduction to R & Review of Expectation and Variance.

Section 2: Estimators.

Section 3: Quality of Estimators.

Section 4: Causality, CI, Quantile.

Section 5: Mid-term Review.

Solution to the extra questions.

Section 6: Likelihood.

Section 7: Fisher's Information.

Section 8: Bayesian.

Section 9: Construction of Estimators.

Section 10: Model Misspecification. (This section was taught by G1 PhD Students.)

Section 11: MLE, MoM & OLS.

Section 12: Hypothesis Testing.

Section 13: Final Review.

Hints to problems.

Note: The notes are prepared with Sanqian Zhang.

Section 3: Bias-variance tradeoff for estimating variance.

Section 3: MSEs of different estimators of correlation.

Section 4: Expected half-widths and coverage probabilities of different estimators of proportion.

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