Statisticians and researchers are most familiar with two types of decision errors that can occur in empirical research using null hypothesis statistical testing (NHST): the false positive (Type I error) and the false negative (Type II error). However, statisticians have also identified another class of epistemic decision errors that also have some (yet-to-be formalized) probability of occurring. In 1957, A. W. Kimball called this class of error as Type III error, whose pithy description was “giving the right answer to the wrong problem” (p. 134). What is more, this error was relevant to all of statistical thinking, not simply NHST decisions. Kimball details a variety of ways in which the right answer to the wrong problem can be given based on the match between theory, ...