Define 'bias' in research.

• A. A random variation in data
• B. A systematic preference or prejudice that can skew results or interpretation
• C. A tool for reducing measurement error
• D. A peer review process

Answer: (B)

Bias in research is a systematic preference or prejudice that can distort both the results and their interpretation. Unlike random variation, which is just natural noise in data, bias tends to push findings in a particular direction, making outcomes appear more favorable or more harmful than they truly are. It isn’t a tool for reducing measurement error; that would undermine validity instead of improving it. And it isn’t the peer review process, which is a quality-control step applied after data are collected.

Think of common forms of bias to see how this works: selection bias happens when the participants studied aren’t representative of the larger population; measurement bias occurs when the instruments or procedures consistently mismeasure in a systematic way; and observer or confirmation bias can arise when researchers’ expectations influence how data are collected or interpreted. Because bias can skew results, researchers work to recognize and minimize it through careful design, randomization, blinding, using validated measures, preregistration, and other methodological safeguards.