Question 5 (Muttiple Choice Worth 2 points) (04.01 LC) Each person in a simple random sample of 1,200 received a survey, and 325 people returned their survey. How could nonresponse cause the results of the survey to be biased? Those who did not respond reduced the sample size, and small samples have more bias than large samples. Those who did not respond may differ in some important way from those who did respond. Those who did not respond caused a violation of the assumption of independence. Those who did not respond are indistinguishable from those who did not receive the survey. Those who did not respond represent a stratum, changing the random sample into a stratified random sample. You must check the box below prior to submitting your exam!

When analyzing survey responses, understanding nonresponse bias is crucial! If a significant portion of those who received the survey doesn’t respond, it’s possible that the nonresponders hold different views or characteristics than those who do. For instance, if mostly younger individuals filled it out, the results may skew toward younger perspectives, making the sample unrepresentative of the entire population. To mitigate bias from nonresponses, consider sending reminders or incentives to encourage participation. Additionally, conducting follow-up surveys with a few nonresponders could identify significant differences between the two groups. This could provide insight into why some people didn’t respond and help adjust the findings for accuracy!