When testing which of multiple causes (e.g., medicines) works the best, the testing sequence has important implications for the validity of the final judgment. Trying one cause for a period of time is important if the cause has tolerance, sensitization, delay, or carryover effects (TSDC). Alternating between the causes is important in autocorrelated environments – when the outcome naturally comes and goes in waves. Across two studies, participants’ beliefs about TSDC influenced the amount of alternating; however, their beliefs about autocorrelation had a very modest effect on the testing strategy. This research helps chart how well people adapt to various environments in order to optimize learning, and it suggests that in situations with no TSDC effects and high autocorrelation, people may not alternate enough

Making judgments by relying on beliefs about causal relations is a fundamental aspect of everyday cognition. Recent research has identified two ways that human reasoning seems to diverge from optimal standards; people appear to violate the Markov Assumption, and do not to “explain away” adequately. However, these habits have rarely been tested in the situation that presumably would promote accurate reasoning – after experiencing the multivariate distribution of the variables through trial-by-trial learning, even though this is a standard paradigm. Two studies test whether these habits persist 1) despite adequate learning experience, 2) despite incentives, and 3) whether they also extend to situations with continuous variables