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University of Hong Kong
1. Overview: random sample; sampling distributions of statistics; moment generating function; large-sample theory: laws of large numbers and Central Limit Theorem; likelihood; sufficiency; factorisation criterion;
2. Estimation: estimator; bias; mean squared error; standard error; consistency; Fisher information; Cramer-Rao Lower Bound; efficiency; method of moments; maximum likelihood estimator;
3. Hypothesis testing: types of hypotheses; test statistics; p-value; size; power; likelihood ratio test; Neyman-Pearson Lemma; generalized likelihood ratio test; Pearson chi-squared test; Wald tests;
4. Confidence interval: confidence level; confidence limits; equal-tailed interval; construction based on hypothesis tests.
Examination One 2-hour written examination 75%
Assignments Coursework (assignments, tutorials and a class test) 25%
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