The difference between the observed values of a variable and the long-run average of the observed values in repetitions of the measurement is (the)
A)nonresponse error.
B)nonsampling error.
C)sampling error.
D)noncoverage error.
E)office error.

Question

Quizplus · Accepted Answer

Sampling error refers to the difference between the observed values and the long-run average in repetitions of a measurement due to the random nature of the sampling process. Nonresponse error occurs when individuals selected for the sample do not respond, while nonsampling error includes all other errors not related to the sampling process (e.g. measurement error, processing error). Noncoverage error occurs when some individuals in the population are not included in the sampling frame, and office error is a type of measurement error that occurs during data collection or processing.

The Difference Between the Observed Values of a Variable and the Long-Run