By Russell G. Almond,Robert J. Mislevy,Linda Steinberg,Duanli Yan,David Williamson
Bayesian inference networks, a synthesis of facts and professional platforms, have complicated reasoning below uncertainty in drugs, company, and social sciences. This cutting edge quantity is the 1st finished therapy exploring how they are often utilized to layout and study leading edge academic assessments.
Part I develops Bayes nets’ foundations in review, information, and graph thought, and works during the real-time updating set of rules. half II addresses parametric kinds to be used with evaluation, model-checking recommendations, and estimation with the EM set of rules and Markov chain Monte Carlo (MCMC). a distinct characteristic is the volume’s grounding in Evidence-Centered layout (ECD) framework for overview layout. This “design ahead” technique allows designers to take complete benefit of Bayes nets’ modularity and talent to version advanced evidentiary relationships that come up from functionality in interactive, technology-rich tests akin to simulations. half III describes ECD, situates Bayes nets as an fundamental component to a principled layout method, and illustrates the tips with an in-depth examine the BioMass venture: An interactive, standards-based, web-delivered demonstration review of technological know-how inquiry in genetics.
This publication is either a source for execs attracted to evaluate and complicated students. Its transparent exposition, worked-through numerical examples, and demonstrations from actual and didactic functions offer worthy illustrations of the way to exploit Bayes nets in academic review. workouts persist with every one bankruptcy, and the net significant other website offers a thesaurus, info units and challenge setups, and hyperlinks to computational resources.
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Additional info for Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences)
Bayesian Networks in Educational Assessment (Statistics for Social and Behavioral Sciences) by Russell G. Almond,Robert J. Mislevy,Linda Steinberg,Duanli Yan,David Williamson
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