What is a potential consequence of sampling bias that overrepresents daring individuals?

What is a potential consequence of sampling bias that overrepresents daring individuals?

• A. It biases estimates of behavioral traits because the sample overrepresents risk-taking individuals.
• B. It yields more accurate estimates of population size.
• C. It has no impact on trait estimates.
• D. It represents all behavioral types equally.

Answer: (A)

When a sample overrepresents daring individuals, the data come from a subset that doesn’t reflect the whole population. This sampling bias makes estimates of behavioral traits biased, because risk-taking data are pulled from people who are more willing to take risks than average. As a result, the average level of daring and the overall distribution of risk-related traits will appear higher than they truly are in the population. This misleads conclusions about how common bold behaviors are or how these traits relate to other factors, unless the bias is addressed. In contrast, population size estimates aren’t inherently improved by having more daring individuals in the sample, and the idea that all behavioral types are represented equally is contradicted by the overrepresentation itself. So the correct consequence is that trait estimates become biased due to the overrepresentation of risk-taking individuals.

When a sample overrepresents daring individuals, the data come from a subset that doesn’t reflect the whole population. This sampling bias makes estimates of behavioral traits biased, because risk-taking data are pulled from people who are more willing to take risks than average. As a result, the average level of daring and the overall distribution of risk-related traits will appear higher than they truly are in the population. This misleads conclusions about how common bold behaviors are or how these traits relate to other factors, unless the bias is addressed. In contrast, population size estimates aren’t inherently improved by having more daring individuals in the sample, and the idea that all behavioral types are represented equally is contradicted by the overrepresentation itself. So the correct consequence is that trait estimates become biased due to the overrepresentation of risk-taking individuals.