Research and Evaluation Exam 1 Practice

Nonresponse bias happens when the people who respond to a survey differ in important ways from those who don’t respond, so the results don’t accurately reflect the whole population. Because the analysis only sees the answers from respondents, any systematic differences between respondents and nonrespondents can skew estimates. That’s why weighting responses to match known population characteristics or following up with nonrespondents to boost representativeness are common ways to address it.

The other options don’t describe nonresponse bias. Misentered data is a data-quality error, not a bias arising from who responds. A too-large sample size doesn’t create bias by itself; it just affects precision. And anonymity can affect response rates but doesn’t define bias from differences between respondents and nonrespondents.