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Direct linkSatake, Eiki; Amato, Philip P. – AMATYC Review, 2008
This paper presents an alternative version of formulas of conditional probabilities and Bayes' rule that demonstrate how the truth table of elementary mathematical logic applies to the derivations of the conditional probabilities of various complex, compound statements. This new approach is used to calculate the prior and posterior probabilities…
Descriptors: Mathematical Logic, Probability, Mathematics Instruction, Statistics
Peer reviewedJarrell, Stephen – Mathematics and Computer Education, 1990
Explains a new way of viewing Bayes' formula. Discusses the revision factor and its interpretation. (YP)
Descriptors: Bayesian Statistics, College Mathematics, Computation, Decimal Fractions
Peer reviewedSahai, Hardeo; Reesal, Michael R. – School Science and Mathematics, 1992
Illustrates some applications of elementary probability and statistics to epidemiology, the branch of medical science that attempts to discover associations between events, patterns, and the cause of disease in human populations. Uses real-life examples involving cancer's link to smoking and the AIDS virus. (MDH)
Descriptors: Bayesian Statistics, Epidemiology, Integrated Activities, Mathematical Applications
Li, Yuan H.; Lissitz, Robert W. – Journal of Educational Measurement, 2004
The analytically derived asymptotic standard errors (SEs) of maximum likelihood (ML) item estimates can be approximated by a mathematical function without examinees' responses to test items, and the empirically determined SEs of marginal maximum likelihood estimation (MMLE)/Bayesian item estimates can be obtained when the same set of items is…
Descriptors: Test Items, Computation, Item Response Theory, Error of Measurement
