Read this guide

Follow us to learn and talk about Data Science:

 

Which statistical test should you use?

by Jean-Paul Maalouf, Data scientist

A guide to choosing an appropriate statistical test according to your question and the data you have.

We have written this guide to help you through the choice of an appropriate statistical test according to your question and the data you have.
The guide proposes a formulation the null hypothesis as well as an example in each situation. Conditions of validity of parametric tests are listed in the paragraph following the grid. When available, nonparametric equivalents are proposed. In some situations, parametric tests do not exist and so only nonparametric solutions are proposed.

The displayed tests are the most commonly used tests in statistics. They are all available in XLSTAT. Please notice that the list is not exhaustive, and that many other situations / tests exist.

Summary:

  • Compare locations
  • Compare series of binary data
  • Compare variances
  • Compare proportions
  • Association tests
  • Time series tests
  • Tests on distributions
  • Tests for outliers