Introduction

This is a mini-book on hypothesis testing in statistics. It covers the tests taught in DSCI 552 in the MDS program at UBC.

• Todolist: add more context and information here

The Test Mind Map

mindmap
  root((Frequentist
  Hypothesis 
  Testings
  ))
    Simulation Based<br/>Tests
    Classical<br/>Tests
      (Chapter 1: <br/>Tests for One<br/>Continuous<br/>Population Mean)
        {{Unbounded<br/>Response}}
        {{Proportion between<br/>0 and 1<br/>obtained from a <br/>Binary Response}}
      (Chapter 2: <br/>Tests for Two<br/>Continuous<br/>Population Means)
        Two<br/>Independent<br/>Populations
          {{Unbounded<br/>Responses}}
          {{Proportions between<br/>0 and 1<br/>obtained from two <br/>Binary Responses}}
        Two<br/>Related<br/>Populations or<br/>Measurements
          {{Unbounded<br/>Responses}}
      (Chapter 3: <br/>ANOVA related <br/>Tests for<br/>k Continuous<br/>Population Means)
        {{Unbounded<br/>Responses}}

Figure 1: A general hypothesis testing mind map outlining all techniques explored in this book. Depending on the overall approach to be used, these techniques are divided into two broad categories: classical and simulation-based tests.

The Test Workflow

Figure 2: A classical-based hypothesis testing workflow structured in four substages: general settings, hypotheses definitions, test flavour and components, and inferential conclusions.