Final answer:
Nonresponse bias occurs when certain individuals do not respond to a survey, leading to nonrepresentative samples and skewed results. A low response rate exacerbates this issue, reducing the survey's accuracy and reliability. Additional factors such as contact method and social desirability also influence the survey's outcomes.
Step-by-step explanation:
Nonresponse can cause the results of a survey to be biased if the individuals who choose not to respond have different characteristics or opinions than those who do respond. This difference can lead to a nonrepresentative sample, which might not reflect the true attributes or behaviors of the entire population. For instance, certain groups of people may be less likely to return surveys due to reasons such as lack of interest, time constraints, mistrust in surveys, or simply not receiving the survey due to outdated or inaccurate contact information.
A low response rate, like the 325 out of 1,200 in the example given, can further magnify this issue. If the nonrespondents are systematically different from the respondents, the survey results will be skewed. As detailed in various sources, response rates are declining, and this affects the accuracy and reliability of surveys that utilize methods like random digit dialing, internet surveys, and mail surveys. Moreover, those who do respond may not accurately represent the whole population, leading to incorrect conclusions about the population’s behaviors or preferences.
Finally, methods of contact can introduce selection bias, and the fact that people might not provide accurate responses due to social desirability bias or imperfect memory can complicate the interpretation of survey data.