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This course introduces statistical inference through likelihood, maximum likelihood estimation, information, and hypothesis testing, then surveys Bayesian statistics, exact tests, bootstrapping, and non-parametric tests.
Syllabus
Likelihood | Log likelihood | Sufficiency | Multiple parameters.
Maximum Likelihood Estimation (MLE) | Score equation | Information | Invariance.
Hypothesis testing (ALL YOU NEED TO KNOW!).
Wald test | Likelihood ratio test | Score test.
Bayesian Statistics: An Introduction.
Exact test, Empirical distribution, Bootstrapping.
Non-parametric tests - Sign test, Wilcoxon signed rank, Mann-Whitney.
Taught by
zedstatistics