Which statistical term is referred to as "average squared deviations" in a data set?

The term "average squared deviations" is directly related to the concept of sample variance. In statistics, variance is a measure of how much the values in a data set deviate from the mean. Specifically, sample variance is calculated by taking the average of the squared differences between each data point and the sample mean. This process involves squaring each deviation to ensure that it is non-negative and to give greater weight to larger deviations. Consequently, sample variance quantifies the spread or dispersion of the data set effectively.

In contrast, the population mean represents the average of a set of values but does not account for the dispersion of those values. The range measures the difference between the maximum and minimum values in a data set, which provides limited insight into the overall variability. Sample standard deviation, while related to sample variance, is the square root of the sample variance and is used to express variability in the same units as the original data. Thus, the designation of "average squared deviations" specifically aligns with the definition of sample variance.