Probability and statistics for business decisions: an introduction to managerial economics under uncertainty
Introduction. The problem of decision under uncertainty: Part one. The use of probabilities based directly on Experience; Part two. Simple random processes and derived proabtained by sampling; Part four. The value of additional information; Part five. Objectivist statistics: Teste of significance and comfidence intervals. Appendix Continuous prior distributions for the parameters of bernoulli and paissau processes.
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The Meaning of Probability
Expected Value and Utility
Random Variables and Probability Distributions
62 other sections not shown
actually assessed assigned ball basic random variable batch Bernoulli process bias binomial distribution bracket cent Chapter column compute the expected conditional cost Conditional Expected conditional probability cost of uncertainty cumulative curve decision problem decision rule demand difference elementary events equal exactly example expected monetary value expected profit expected terminal loss expected value Figure formula fractile fraction defective frequency distribution gamma distribution given graph histogram inventory large number likelihood long-run manufacturer measurements method Normal approximation Normal distribution null hypothesis number of defectives number of successes observed obtained ooooo optimal sample package parameter partial expectation perfect information pieces Poisson distribution Poisson process population possible values posterior distribution prior distribution prob probability distribution procedure process average quantity ratio rejection relative frequencies result sampling error Section setup specified standard deviation statistic terminal act terminal action tion total expected loss trials true value unconditional variance weights