top of page

Topics

The course consists of two parts: single and multiple comparisons. All the examples are illustrated using R and the code is a part of the online books. Slides are available only for the first part.

​

R packages:

​

  • library(pwr) 

  • library(equivalence)

​

Useful R functions include:

​

  • t.test()

  • pwr.t.test()

  • wilcox.test()

  • pwilcox()

  • tost()

  • p.adjust()

 

The course in slides format & online books

Slides
​
​
Slides are available for the topic of single comparison and cover the following topics:
​
  • Introduction
  • Student’s t-test
  • One sample t-test
  • One sided test
  • Two sided test
  • Confidence interval for the mean
  • Two samples t-test
  • What should we test?
  • Assuming equal variances
  • Assuming different variances
  • Power of a t-test
  • Mann-Whitney-Wilcoxon test
  • The limited role of the p-value
Online books
 
Part 1: single comparison.
The first part of the online book is focused on single comparison and cover the following topics:

The first part of the online book is focused on single comparison and cover the following topics:
 
  • ​Introduction
  • Student’s t-test
  • One sample t-test
  • One sided test
  • Two sided test
  • Confidence interval for the mean
  • Two samples t-test
  • What should we test?
  • Assuming equal variances
  • Assuming different variances
  • Power of a t-test
  • Mann-Whitney-Wilcoxon test
  • The limited role of the p-value
  • Equivalence tests
  • Introduction
  • Two samples test
  • The TOST procedure
  • Difference testing versus equivalence testing one sample test
​
The last 5 topics are covered in the slides.
Part 2: multiple comparisons.
The second part of the online book is focused on single comparison and cover the following topics:
 
  • Introduction
  • Distribution of the p-values
  • Introduction
  • Single comparison between 2 groups
  • A single comparison… among many others
  • The Bonferroni correction
  • Permutation test
  • Controlling the False Discovery Rate
  • Detecting associations
  • A Monte Carlo simulation
bottom of page