Mathematical psychology
Mathematical psychology is a sub-discipline of psychology which - in contrast to other sub-disciplines - is defined by its working methods and not by its subject.
In mathematical psychology, psychological models are mathematically formalized and described, e.g. B. in psychological scaling, often for psychometric applications , in psychophysics , signal discovery theory, in the form of learning models , in the psychology of knowledge , decision theory or perceptual psychology , but also in information theory, e.g. B. to measure the novelty value of news, or also in social psychology , clinical psychology as well as in work and organizational psychology . Especially in cognitive psychology , multinomial processing tree models (MVB) have proven themselves. For the analysis of reaction times and the frequency of correct answers in simple binary decision-making tasks, random walk models have recently been increasingly used. The diffusion model (R. Ratcliff, 1978) is mathematically formalized as a continuous random walk process (see Wiener process ). Similar equations can be found in physical models of Brownian molecular motion . Mostly probabilistic models are used, but deterministic models can also be found . The mathematical formalizations have the advantage that they allow more precise predictions - and can thus also be subjected to more stringent empirical tests. Theoreticians are thus forced to give precise and explicit formalizations and operationalizations of hypothetical processes.
The background is an understanding of psychology as an experimental or empirical natural science . This view is a direct result of the basic understanding of psychology as it was understood by its pioneers ( Wilhelm Wundt , Gustav Theodor Fechner , Karl Pearson , Hermann Ebbinghaus , Alfred Binet , Charles Spearman , William Stern and many others). Since the Second World War, psychology has also increasingly developed in social science. The connection to a faculty (humanities, natural or social sciences) says nothing about the orientation of the department, as this is usually justified purely historically or administratively.
Central journals are Psychometrika , the Journal of Mathematical Psychology and the British Journal of Mathematical and Statistical Psychology , and there are also numerous publications in Mathematical Social Sciences . In the US there is a Society for Mathematical Psychology , which holds annual meetings; in Europe there is the (informal) European Mathematical Psychology Group (EMPG), also with annual meetings.
literature
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About mathematical psychology
- Falmagne, J.-Cl. (2005). Mathematical psychology - A perspective. Journal of Mathematical Psychology, 49, 436-439.
- Luce, RD (Ed.) (1963). Handbook of Mathematical Psychology. New York: Wiley. [Vol. 1 & 2: 1963, Vol. 3: 1965]
- Wendt, D. (1988). Mathematical psychology. In R. Asanger & G. Wenninger (Eds.), Concise Dictionary of Psychology. Weinheim: PVU.
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Textbooks on mathematical psychology
- Coombs, CH, Dawes, RM & Tversky, A. (1970). Mathematical psychology - an elementary introduction. Englewood Cliffs, NJ: Prentice Hall
- Deppe, W. (1976). Formal models in psychology. An introduction. Stuttgart: Kohlhammer.
- Heath, RA (2000). Nonlinear dynamics: Techniques and applications in psychology. Mahwah, NJ: Erlbaum.
- Kempf, W. & Andersen, EB (Ed.) (1977). Mathematical models for social psychology. Bern: Huber.
- Restle, F. & Greeno, J. (1970). Introduction to Mathematical Psychology. Reading. MA: Addison-Wesley.
- Sixtl, F. (1996). Introduction to Exact Psychology. Munich; Vienna: Oldenbourg.
- Sydow, H. & Petzold, P. (1982). Mathematical psychology. Mathematical modeling and scaling in psychology. Berlin: Springer, ISBN 978-3540113393 .
- Townsend, JT, & Ashby, FG (1983). Stochastic modeling of elementary psychological processes. Cambridge: Cambridge University Press.