Bayesian confirmation theory is a leading theory to decide the confirmation/refutation of a hypothesis based on probability calculus. While it may be much discussed in philosophy of science, is it actually practiced in terms of hypothesis testing by scientists? Since the assignment of some of the probabilities in the theory is open to debate and the risk of making the wrong decision is unknown, many scientists do not use the theory in hypothesis testing. Instead, they use alternative statistical tests that (...) can measure the risk or the reliability in decision making, circumventing some of the theoretical problems in practice. Therefore, the theory is not very popular in hypothesis testing among scientists at present. However, there are some proponents of Bayesian hypothesis testing, and software packages are made available to accelerate utilization by scientists. Time will tell whether Bayesian confirmation theory can become both a leading theory and a widely practiced method. In addition, this theory can be used to model the belief of scientists when testing hypotheses. (shrink)

We developed and tested a behavioral version of the Defining Issues Test-1 revised (DIT-1r), which is a measure of the development of moral judgment. We conducted a behavioral experiment using the behavioral Defining Issues Test (bDIT) to examine the relationship between participants’ moral developmental status, moral competence, and reaction time when making moral judgments. We found that when the judgments were made based on the preferred moral schema, the reaction time for moral judgments was significantly moderated by the moral developmental (...) status. In addition, as a participant becomes more confident with moral judgment, the participant differentiates the preferred versus other schemas better particularly when the participant’s abilities for moral judgment are more developed. (shrink)