The Institute for Mathematical Behavioral Sciences Colloquium Series presents
“Probabilistic Contextuality of Top Direct Cross-Influences: A General Theory”
with Ehtibar Dzhafarov, Professor of Psychological Sciences, Purdue University
Thursday, October 9, 2014
Social Science Plaza A, Room 2112
Probabilistic Contextuality is a notion primarily used in foundations of quantum mechanics, but it is applicable to all areas of research where systems with random outputs are recorded in response to deterministic inputs. Psychology, with its response variables almost always random, is one of these areas. The notion of Probabilistic Contextuality relates to two foundational issues in the Kolmogorovian Probability Theory: the issue of identity of random variables (as distinct from their distributions), and the issue of “sewing together” (probabilistically coupling) random variables conditioned on different, mutually incompatible conditions. In a nutshell, Probabilistic Contextuality is introduced as follows. One hypothesizes that input x affects only output A and input y affects only output B. This hypothesis may be upheld or rejected by means of one of numerous tests (in psychology, they are called tests for selective influences, and they include, as a subset, the tests used in quantum mechanics). If the hypothesis of selectiveness is wrong, there are two possibilities: either the violations of selectiveness can be explained by Cross-Influences (e.g., A is influenced by both x and y "directly"), or this is not the case. This latter case is the one when we speak of Probabilistic Contextuality. I will discuss new developments that allow one to define and measure both Cross-Influences and Probabilistic Contextuality. Dzhafarov will also present empirical evidence suggesting that human behavior (unlike that of elementary particles) may be void of contextuality.
For further information, please contact Joanna Kerner, email@example.com or 949.824.8651.