I personally prefer
to think of DF as a kind of statistical currency. You earn it by
taking independent sample units, and you spend it on estimating
population parameters or on information required to get compute test
statistics.
In this article,
degrees of freedom are explained through these lenses through some common hypothesis
tests, with some selected topics like saturation, fractional DF, and
mixed effect models at the end.