Delves into hypothesis testing, covering test statistics, critical regions, power functions, p-values, multiple testing, and non-parametric statistics.
Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.
