9  Module 9: ANOVA and multiple hypothesis testing

Learning objectives

• Run a simple one-way ANOVA, without knowing the details of the test (the level of detail required is what’s presented in the blog post).

• Apply FDR or Bonferroni correction to control the errors when performing multiple hypothesis testing.

• The value of presenting an entire distribution as a prediction.

9.1 Proposed structure of this chapter

9.2 Introduction

• objective of ANOVA
• why we can’t use test statistics learned previously
  • solution look at variance in sample means
• motivating example for within and between group variance with boxplot

9.3 Hypothesis test steps

Note: order of steps should follow previous chapter - hypotheses - assumptions - SST and SSE (include pictures motivating what the formula) - ANOVA table - introduce F distribution - F-statistic - Finding p-value + critical value