The normal, expected difference between a statistic and a parameter is called
A) sampling error
B) bias
C) controlled randomization
D) none of these, since statistics and parameters may never differ

Question

Quizplus · Accepted Answer

Sampling error refers to the natural variability that occurs when a sample is used to estimate a population parameter. Therefore, it is the normal, expected difference between a statistic (based on the sample) and a parameter (based on the population). Bias and controlled randomization are not necessarily related to the difference between statistics and parameters. The last option is incorrect because statistics and parameters may differ due to sampling error.

The Normal, Expected Difference Between a Statistic and a Parameter