Previous research on Bayesian reasoning has typically investigated people’s
ability to assess a posterior probability (i.e., a positive predictive value) based on
prior knowledge (i.e., base rate, true-positive rate, and false-positive rate). In this
article, we systematically examine the extent to which people understand the
effects of changes in the three input probabilities on the positive predictive value,
that is, covariational reasoning. In this regard, two different operationalizations
for measuring covariational reasoning (i.e., by single-choice vs. slider format) are
investigated in an empirical study with N = 229 university students. In addition, we
aim to answer the question wheter a skill in “conventional” Bayesian reasoning is
a prerequisite for covariational reasoning