College Entrance Exams Example
This chapter highlights an example of Bayesian Belief Network (BBN) in an academic scenario by evaluating the variables of “Freshman Status” and “ACT Scores.” Here, student retention has great human capital economic utility in the university’s ability to
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Jeff Grover
Strategic Economic Decision-Making Using Bayesian Belief Networks to Solve Complex Problems 123
SpringerBriefs in Statistics
For further volumes: http://www.springer.com/series/8921
Jeff Grover
Strategic Economic Decision-Making Using Bayesian Belief Networks to Solve Complex Problems
Jeff Grover Maple Crest Way 512 Elizabethtown, Kentucky, USA
ISSN 2191-544X ISSN 2191-5458 (electronic) ISBN 978-1-4614-6039-8 ISBN 978-1-4614-6040-4 (eBook) DOI 10.1007/978-1-4614-6040-4 Springer New York Heidelberg Dordrecht London Library of Congress Control Number: 2012951657 # Springer Science+Business Media New York 2013 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Exempted from this legal reservation are brief excerpts in connection with reviews or scholarly analysis or material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. Duplication of this publication or parts thereof is permitted only under the provisions of the Copyright Law of the Publisher’s location, in its current version, and permission for use must always be obtained from Springer. Permissions for use may be obtained through RightsLink at the Copyright Clearance Center. Violations are liable to prosecution under the respective Copyright Law. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Sergeant First Class Charles V. Lang, IV (U.S. Army, Retired) “Friend”
Contents
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2
An Introduction to Bayes’ Theorem and Bayesian Belief Networks (BBN) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1 Introduction to Bayes’ Theorem and BBN . . . . . . . . . . . . . . . . . 1.2 The Identification of the Truth . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 The Motivation for This Book . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 The Intent of This Book . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.5 The Utility of Bayes’ Theorem .
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