Assumptions of parametric tests
Parametric tests make assumptions about population data that require the statistics practitioner to perform analysis of data prior to modeling, especially when using sample data because the sample statistics are leveraged as estimates for the population parameters when the true population parameters are unknown. These are the three primary assumptions of parametric hypothesis tests:
- Normally distributed population data
- Samples are independent
- Equal population variances (when comparing two or more groups)
In this chapter, we discuss the z-test, t-test, ANOVA, and Pearson’s correlation. These tests are used on continuous data. In addition to these assumptions, Pearson’s correlation requires data to contain paired samples. In other words, there must be an equal number of samples in each group being compared as Pearson’s correlation is based on pairwise comparisons.
While these assumptions are ideal, there are...
