# Degrees of Freedom Tutorial

A lot of researchers seem to be struggling with their understanding of the statistical concept of degrees of freedom. Most do not really care about why degrees of freedom are important to statistical tests, but just want to know how to calculate and report them. This page will help. For those interested in learning more about degrees of freedom, take a look at the following resources:

- This chapter in the little handbook of statistical practice
- Walker, H. W. (1940). Degrees of Freedom.
*Journal of Educational Psychology, 31(4)*, 253-269.

I couldn’t find any resource on the web that explains calculating degrees of freedom in a simple and clear manner and believe this page will fill that void. It reflects my current understanding of degrees of freedom, based on what I read in textbooks and scattered sources on the web. Feel free to add or comment.

### Conceptual Understanding

Let’s start with a simple explanation of degrees of freedom. I will describe how to calculate degrees of freedom in an *F*-test (ANOVA) without much statistical terminology. When reporting an ANOVA, between the brackets you write down degrees of freedom 1 (df1) and degrees of freedom 2 (df2), like this: “*F*(df1, df2) = …”. Df1 and df2 refer to different things, but can be