Psychological mechanisms underlying the biased interpretation of numerical scientific evidence

Do people use their statistical expertise selectively to reach preferred conclusions when evaluating scientific evidence, with those more expert showing more preferential bias? We investigated this motivated numeracy account of evidence evaluation but came to a different account for biased evaluation. Across three studies (N = 2,799), participants interpreted numerical data from gun control intervention studies. In Studies 1 and 2, participants reached accurate conclusions more frequently from scientific data when those data aligned with their political preferences than when they did not, an attitude congeniality effect. This bias was unrelated to numerical ability (i.e., numeracy) and cognitive effort, although each variable predicted correct reasoning independently. Probing further, we found that attitude congeniality did not prompt people to discover valid statistical rationales for their more frequent correct conclusions. Rather, people came to right conclusions more often but for wrong reasons, suggesting why numerical ability need not be related to the congeniality effect. In Study 2, we showed this pattern was not due to forced guessing. In Study 3, we showed that the rationales, whether right or wrong, carried some weight over multiple scenarios, indicating that participants were not just expressive responding-that is, simply stating preferred conclusion regardless of the data. Statistical training did not reduce attitude congeniality biases. We suggest that people engage in "expressive rationalization" rather than "rationality" to reach preferred conclusions, finding convenient rationales for preferred conclusions that need not be valid, even though they can lead to conclusions that are. (PsycInfo Database Record (c) 2025 APA, all rights reserved).