## A primer on decision analysis for individually prescribed instructionResearch and Development Division, American College Testing Program, 1973 - Decision making - 100 pages |

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advance or retain advance the student applications assume average or expected Bayes theorem black box coherence computation consider constants correctly classifying critical posterior mean cutting score decision analysis decision maker decision problem decision theory denoted determine distribution of 9 equivalent expected loss expected or average expected utility expected value extensive form analysis families of utility given increases Individually Prescribed Instruction integral linear utility function loss function mastery level minimizes the expected model density moment-generating function nonmaster normal distribution normal form analysis Novick number of tasks outcomes pairs parameter partition paX(l percentile rank positive linear transformation possible posterior distribution posterior variance PR(z preposterior analysis prior information prior probability distribution probability mass function quadratic utility random variable reasonable decision rules Reparameterization retain the student risk function sample information Section 2.3 situation summarized symbol Table test score threshold utility total Bayes risk u(di value of sample