Sampling Error Versus Non Sampling Error – UGC NET Question

Sampling error is the random difference between values obtained from a sample and the true values in the population. It occurs because the sample, even if selected properly, represents only a subset of the population. As a result, estimates like means or proportions fluctuate from sample to sample. Larger and more representative samples reduce sampling error but cannot eliminate it entirely.

Option A:
Option A describes errors arising from mistakes in coding or tabulation, which are classified as non sampling errors. These can occur even in a census where the whole population is measured.

Option B:
Option B correctly explains sampling error as the natural variation due to observing only a part of the population. It captures the essence of random fluctuation inherent in the sampling process and is consistent with statistical theory.

Option C:
Option C refers to deliberate response distortion or bias, which again falls under non sampling errors, specifically response bias. While serious, it is conceptually distinct from sampling error.

Option D:
Option D deals with faulty instruments, another form of non sampling error because it affects measurement irrespective of whether a sample or census is used.