A short, 5-page document from a Mayo Clinic statistician providing a clear description of non-parametric testing compared to parametric testing.
What the article offers
This short article explains the differences between parametric and non-parametric statistical tests. An example illustrates how using an inappropriate procedure can lead to erroneous conclusions. A list of common parametric statistical tests and their non-parametric counterparts is given as well as guidance on when to use each approach. (Note: The hyperlink to a previous document in the series does not work.)
Who created it
Tanya Hoskin, MS, a statistician in the Mayo Clinic Department of Health Sciences Research who provides consultations through the Mayo Clinic Center for Clinical and Translational Science’s biostatistical consulting unit. This document is one of a series developed to explain key statistical concepts to non-statisticians.