Pathology

Blinding

Mathematics

Statistical hypothesis testing

Statistics

Variety (cybernetics)

Econometrics

Cognitive psychology

Artificial intelligence

Null hypothesis

Psychology

Economics

Computer science

Significance testing

Statistical evidence

Clinical trial

Medicine

Management Science

Statistical training helps individuals analyze and interpret data. However, the emphasis placed on null hypothesis significance testing in academic training and reporting may lead researchers to interpret evidence dichotomously rather than continuously. Consequently, researchers may either disregard evidence that fails to attain statistical significance or undervalue it relative to evidence that attains statistical significance. Surveys of researchers across a wide variety of fields (including medicine, epidemiology, cognitive science, psychology, business, and economics) show that a substantial majority does indeed do so. This phenomenon is manifest both in researchers’ interpretations of descriptions of evidence and in their likelihood judgments. Dichotomization of evidence is reduced though still present when researchers are asked to make decisions based on the evidence, particularly when the decision outcome is personally consequential. Recommendations are offered. This paper was accepted by Yuval Rottenstreich, judgment and decision making.

Blinding Us to the Obvious? The Effect of Statistical Training on the Evaluation of Evidence