UGC NET Questions (Paper – 1)

Non-response bias occurs when the characteristics of non-respondents differ in important ways from those of respondents, leading to distorted estimates of population parameters. For example, if less satisfied individuals are less likely to answer a satisfaction survey, the results will be overly positive. This bias persists even with large sample sizes if non-response is systematic. Therefore, the bias described in the stem is correctly termed non-response bias.

Option A:
Sampling bias refers more broadly to systematic errors in the way the sample is selected, such as excluding certain groups entirely, but it does not specifically focus on the difference between respondents and non-respondents. Non-response is one particular source of sampling error, so sampling bias is too general here.

Option B:
Measurement bias arises when instruments or questions systematically overestimate or underestimate the true values, for instance due to poorly worded items or faulty devices. It is unrelated to whether people choose to respond or not. Hence, measurement bias is not the appropriate completion.

Option C:
Non-response bias undermines the representativeness of survey findings because missing data are not random but correlated with variables of interest. Strategies such as follow-up contacts or weighting adjustments are often used to reduce its impact. These aspects fit exactly with the description in the question.

Option D:
Response-set bias involves patterns such as acquiescence or social desirability in the way respondents answer questions, affecting the quality of obtained responses rather than whether people respond at all. Therefore, response-set bias does not match the situation described in the stem.