Handbook

This course introduces students to the field of statistical inference including the main parametric and non-parametric techniques. During seminars and tutorials a range of topics will be introduced including uniformly minimum variance estimation, Cramer-Rao inequality, Lehmann-Scheffe theorem, monotone likelihood ratio distributions and uniformly most powerful unbiased tests, generalised likelihood ratio tests, exact tests and large sample tests, Bayesian point estimation, interval estimation and hypothesis testing, robustness and bootstrap resampling, order statistics, goodness of fit, contingency tables, statistical inference based on ranks, one sample, two sample and k-sample problems, blocked data, independence and association.