7  Module 7: Hypothesis testing based on distributional assumptions

Learning objectives

  • Describe the t-distribution family and its relationship with the normal distribution. (Move to module 5)

  • Use results from the assumption of normality or the Central Limit Theorem to perform estimation and hypothesis testing.

  • Compare and contrast the parts of estimation and hypothesis testing that differ between simulation- and resampling-based approaches with the assumption of normality or the Central Limit Theorem-based approaches.

  • Write a computer script to perform hypothesis testing based on results from the assumption of normality or the Central Limit Theorem.

  • Discuss the potential limitations of these methods.

7.1 Proposed structure of this chapter

Introduction

  • recall diff between simulation vs traditional methods
  • recall general steps of hypothesis testing - same steps as before. Highlight where differences are
  • Z score to motivate test statistic?

Hypothesis test for one proportion

  • Note: order of these tests presented should follow Ch 5, steps of hypothesis test should be same as ch 6
  • recall sampling dist for one proportion
  • assumptions
  • Null distribution under assumption
  • Find test statistic
  • Find P-value

Hypothesis test for one mean

Hypothesis test for two proportions

Hypothesis test for two means

  • independent vs dependent