Simplicity and Goodness-of-Fit in Explanation: The Case of Intuitive Curve-Fitting

Proceedings of the 36th Annual Meeting of the Cognitive Science Society, CogSci 2014

Volumn , Issue , 2014, Pages 701-706

  Johnson, Samuel G B ^a   Jin, Andy ^b   Keil, Frank C ^a  

^a YALE UNIVERSITY   (United States)

^b The University of North Carolina at Chapel Hill   (United States)

Author keywords

causal reasoning; diagnostic reasoning; Explanation; intuitive statistics; simplicity

Indexed keywords

CAUSAL REASONING; CURVES FITTINGS; DIAGNOSTIC REASONING; EXPLANATION; GOODNESS OF FIT; INTUITIVE STATISTIC; MOST LIKELY; OBSERVED DATA; SIMPLE++; SIMPLICITY;

CURVE FITTING;

EID: 85050890043     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. Bonawitz, E.B., & Lombrozo, T. (2012). Occam's rattle: Children's use of simplicity and probability to constrain inference. Developmental Psychology, 48, 1156-1164.
2. Forster, M., & Sober, E. (1994). How to tell when simpler, more unified, or less ad hoc theories will provide more accurate predictions. The British Journal for the Philosophy of Science, 45, 1-35.
3. Kline, R.B. (1998). Principles and practice of structural equation modeling (1st Ed.). New York: Guilford Press.
4. st Annual Conference of the Cognitive Science Society (pp. 1157-1162). Austin, TX: Cognitive Science Society.
5. Lombrozo, T. (2007). Simplicity and probability in causal explanation. Cognitive Psychology, 55, 232-257.
6. Weisberg, D.S., Keil, F.C., Goodstein, J., Rawson, E., & Gray, J.R. (2008). The seductive allure of neuroscience explanations. Journal of Cognitive Neuroscience, 20, 470-477.