Degrees of Freedom
Estimates of
parameters can be based
upon different amounts of information. The number of independent
pieces of information that go into the estimate of a parameter is
called the degrees of freedom (df). In general, the degrees of
freedom of an estimate is equal to the number of independent scores
that go into the estimate minus the number of parameters estimated as
intermediate steps in the estimation of the parameter itself. For
example, if the
variance, σ², is
to be estimated from a random sample of N independent scores, then the
degrees of freedom is equal to the number of independent scores (N)
minus the number of parameters estimated as intermediate steps (one,
μ estimated by M) and is therefore equal to N-1.