The observed value of a statistic will differ from sample to sample.This phenomenon is known as:
A)the sampling distribution
B)sampling error
C)sampling bias
D)sampling variability
E)None of these

Question

Quizplus · Accepted Answer

The term "sampling variability" refers to the fact that different random samples from the same population will generally produce different values of a given statistic, due to chance variation in the selection of individuals for each sample. This is distinct from sampling error, which refers to systematic deviations between sample values and a true population parameter. The sampling distribution is a theoretical construct that describes the distribution of statistic values that would be obtained from all possible samples of a given size from a population. Sampling bias refers to deviations from randomness in the selection of individuals for a sample, which can lead to systematic errors in estimating population parameters. Therefore, the best choice to describe the observed variation in sample statistic values from sample to sample is D, sampling variability.

The Observed Value of a Statistic Will Differ from Sample