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You are here: Home / beliefs-uncertainty-inference / Bayesian (inverse probability) inference in games : Part two

May 25, 2013 by jagfnz Leave a Comment

Bayesian (inverse probability) inference in games : Part two

The second of two sceencast lectures on how intelligent players reason about states and signals in a game ; the first is here
This lecture uses the two practise problems from class (one on breast cancer screening, the other on witness reports in a courtroom case) to develop a “language” of probability in a way  that is (1) easily understandable for ANY type or level of student – whether trained in statistics or not and (2) useful for students of game theory . Simple numerical examples using Gigerenzer style natural frequency/count reasoning are developed to explain a wide range of concepts connecting uncertainties about “states” and “signals” sensitivity, specificity, conditional probabilities, predictive probabilities, inverse probabilities, etc.

Filed Under: beliefs-uncertainty-inference, Econ 223 2013 Tagged With: bayes theorem, Econ 223 2013, economics, game theory, inductive inference, inverse probability

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