Explores the challenges of multiple testing in genomic data analysis, covering error rate control, adjusted p-values, permutation tests, and pitfalls in hypothesis testing.
Delves into hypothesis testing, covering test statistics, critical regions, power functions, p-values, multiple testing, and non-parametric statistics.
Explores t-tests, confidence intervals, ANOVA, and hypothesis testing in statistics, emphasizing the importance of avoiding false discoveries and understanding the logic behind statistical tests.
