The Science of Mistakes
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The Operational Model Of Mistakes: Economic Data Engineering And Mistakes; Operationalizing Bayesian Expected Utility Theory; Operationalizing Costs Of Learning; Finding All Rationalizations; Cost Recovery And Qualifying Utility Functions; Special Cost Functions; Comparison Of Revealed Experiments; Openings And Closings; The Shannon Model Of Rational Inattention: Two Solution Methods And Their Uses; The Invariant Likelihood Ratio Hyperplanes And Consideration Sets; Equilibrium, Exchangeability, And Symmetry; Applications: Inverse Machine Learning; Productive Efficiency, Management, And Income; Survey-Based Data Engineering And Mistakes; Psychometric Choice Theory; Inverse Human Learning
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