What term refers to the number of values in a calculation of a statistic that are free to vary?

Degrees of freedom is a fundamental concept in statistics that indicates the number of independent values or quantities that can vary in an analysis without violating any predetermined constraints. This term is particularly important when estimating statistical parameters or when conducting hypothesis tests.

For instance, in the context of a sample mean, if you have a sample of n observations, you typically have n - 1 degrees of freedom when you calculate certain statistics, such as sample variance. This is because one value is constrained by the mean of the sample, which means it cannot vary freely; the others can.

This concept helps in determining the appropriate distribution to use when making inferences about a population based on a sample. It essentially accounts for the restrictions imposed by the sample size and ensures that the statistical calculations and resulting conclusions are valid.

The other terms listed are specific statistical measures or methodologies but do not represent the concept of varying values within a statistical calculation. For example, average deviation and average absolute deviation pertain to measures of dispersion, while standard error is related to the estimation of the accuracy of a sample statistic. None of these capture the essence of how many values can vary independently in a given calculation.