Sampling error definition – UGC NET Question

Sampling error is the natural discrepancy between a statistic computed from a sample and the true but unknown population parameter. It occurs because a sample, no matter how well drawn, captures only part of the population’s variability. As sample size increases and sampling procedures are sound, sampling error tends to decrease. Thus, the difference described in the stem is correctly termed sampling error.

Option A:
Measurement error arises from inaccuracies in instruments, data recording or respondent misunderstanding and is not solely due to using a subset of the population. It reflects flaws in measurement rather than in sampling.

Option B:
Non-response error occurs when certain selected individuals do not participate, potentially biasing results if non-respondents differ systematically from respondents. While related to sampling, it is a specific type of non-sampling error.

Option C:
Response bias refers to systematic tendencies for respondents to answer inaccurately, such as social desirability bias, and is independent of whether a sample or census is used. It is not the error defined here.

Option D:
Sampling error arises even under proper random sampling and is expected whenever one uses a sample instead of a census. It is the discrepancy highlighted in the stem, making this option correct.