Which term refers to a measure of the variability of the means of a sample?

The term that best refers to a measure of the variability of the means of a sample is indeed the standard deviation of the mean, which is often abbreviated as the standard error of the mean. The standard error quantifies how much the sample means would vary if you were to take multiple samples from the same population. It indicates the precision of the sample mean as an estimate of the population mean.

The standard deviation itself measures the spread of individual data points around the mean of a single dataset, but when we are specifically referring to the variability of sample means, the appropriate term is the standard error (often termed as the standard deviation of the means). This measure plays a crucial role in inferential statistics, particularly when constructing confidence intervals or conducting hypothesis tests.

The other terms do not accurately describe the specific concept of variability in the context of sample means. For example, residual variance relates to the differences between observed and predicted values in regression analysis, while mean variability and score variance do not have established definitions that specifically correlate with the variability of means in a statistical context.