About a year ago, a reader asked if I could try to explain degrees of freedom in statistics. Since then, I’ve been circling around that request very cautiously, like it’s some kind of wild beast that I’m not sure I can safely wrestle to the ground.

Degrees of freedom aren’t easy to explain. They come up in many different contexts in statistics—some advanced and complicated. In mathematics, they're technically defined as the dimension of the domain of a random vector.

But we won't get into that. Because degrees of freedom are generally not something you need to understand to perform a statistical analysis—unless you’re a research statistician or someone studying statistical theory.

And yet, inquiring minds want to know. So for the adventurous and the curious, here are some examples that provide the basic gist of degrees of freedom in statistics.

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