The sampling distribution’s variability can be measured either by standard deviation, also called “standard error of the mean,” or population variance, depending on the context and inferences you are trying to draw. They both are mathematical formulas that measure the spread of data points in relation to the mean.
There are three primary factors that influence the variability of a sampling distribution. They are:
The number observed in a population: This variable is represented by “N.” It is the measure of observed activity in a given group of data.
The number observed in the sample: This variable is represented by “n.” It is the measure of observed activity in a random sample of data that is part of the larger grouping.
The method of choosing the sample: How the samples were chosen can account for variability in some cases.