Understanding Statistics & Experimental Design

This lecture covers various types of t-tests, including independent samples t-test, one sample t-test, and repeated measures t-test. It also delves into confidence intervals, null hypothesis significance testing, and the importance of avoiding false discoveries in statistical analysis. The instructor explains the logic behind ANOVA, the distribution of F under the null hypothesis, and the strategy for distinguishing between null and alternative hypotheses. Additionally, the lecture discusses the advantages of nonparametric tests, multiple testing, and the pitfalls of Bonferroni correction. Practical examples and worked exercises are provided to illustrate key concepts.