What scenario can mislead interpretation of normative data?

• A. When the sample includes only elite athletes
• B. When an athlete belongs to a non-represented subgroup
• C. When the test is administered under ideal conditions
• D. When the data are from multiple tests

Answer: (B)

Normative data are meaningful only when the person being evaluated matches the population the norms were built from. If an athlete comes from a subgroup that isn’t represented in the normative sample, their score is being compared to a distribution that doesn’t reflect their own characteristics. That mismatch can make their performance seem higher or lower than it truly is within their own context, leading to misleading interpretations. The key idea is representativeness: norms must match the individual’s relevant traits (age, sex, sport, training background, etc.) for the comparison to be valid.