By Russell G. Almond,Robert J. Mislevy,Linda Steinberg,Duanli Yan,David Williamson
Bayesian inference networks, a synthesis of information and professional structures, have complex reasoning lower than uncertainty in drugs, enterprise, and social sciences. This cutting edge quantity is the 1st complete remedy exploring how they are often utilized to layout and research cutting edge academic assessments.
Part I develops Bayes nets’ foundations in overview, records, and graph thought, and works throughout the real-time updating set of rules. half II addresses parametric varieties to be used with review, model-checking concepts, and estimation with the EM set of rules and Markov chain Monte Carlo (MCMC). a special characteristic is the volume’s grounding in Evidence-Centered layout (ECD) framework for evaluate layout. This “design ahead” process permits designers to take complete good thing about Bayes nets’ modularity and talent to version advanced evidentiary relationships that come up from functionality in interactive, technology-rich checks comparable to simulations. half III describes ECD, situates Bayes nets as an essential element of a principled layout strategy, and illustrates the information with an in-depth examine the BioMass undertaking: An interactive, standards-based, web-delivered demonstration overview of technology inquiry in genetics.
This e-book is either a source for pros drawn to evaluate and complicated students. Its transparent exposition, worked-through numerical examples, and demonstrations from actual and didactic purposes supply worthwhile illustrations of ways to exploit Bayes nets in academic review. workouts stick to every one bankruptcy, and the net better half web site offers a word list, facts units and challenge setups, and hyperlinks to computational resources.
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Extra resources 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