Representation facilitates reasoning: what natural frequencies are and what they are not.
A good representation can be crucial for finding the solution to a problem. Gigerenzer and Hoffrage (Psychol. Rev. 102 (1995) 684; Psychol. Rev. 106 (1999) 425) have shown that representations in terms of natural frequencies, rather than conditional probabilities, facilitate the computation of a cause's probability (or frequency) given an effect--a problem that is usually referred to as Bayesian reasoning. They also have shown that normalized frequencies--which are not natural frequencies--do not lead to computational facilitation, and consequently, do not enhance people's performance. Here, we correct two misconceptions propagated in recent work (Cognition 77 (2000) 197; Cognition 78 (2001) 247; Psychol. Rev. 106 (1999) 62; Organ. Behav. Hum. Decision Process. 82 (2000) 217): normalized frequencies have been mistaken for natural frequencies and, as a consequence, "nested sets" and the "subset principle" have been proposed as new explanations. These new terms, however, are nothing more than vague labels for the basic properties of natural frequencies.
Hoffrage
Ulrich
U
Max Planck Institute for Human Development, Lentzeallee 94, 14195, Berlin, Germany. hoffrage@mpib-berlin.mpg.de
Gigerenzer
Gerd
G
Krauss
Stefan
S
Martignon
Laura
L
D001499:Bayes Theorem; D003210:Concept Formation; D006801:Humans; D011337:Probability Learning; D011340:Problem Solving