This course covers statistical inference, including likelihood, sufficiency, maximum likelihood estimation, hypothesis testing, Bayesian statistics, exact tests, bootstrapping, and non-parametric tests. The course aims to teach students how to apply these statistical concepts in practice. The teaching method includes 7 videos with a total duration of 3 hours and 30 minutes. This course is intended for individuals interested in expanding their knowledge of statistical inference and its applications.
Overview
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
