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Probability And Information

Author: David Applebaum
Publisher: Cambridge University Press
ISBN: 9780521555289
Size: 69.20 MB
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This elementary introduction to probability theory and information theory provides a clear and systematic foundation to the subject; the author pays particular attention to the concept of probability via a highly simplified discussion of measures on Boolean algebras. He then applies the theoretical ideas to practical areas such as statistical inference, random walks, statistical mechanics, and communications modeling. Applebaum deals with topics including discrete and continuous random variables, entropy and mutual information, maximum entropy methods, the central limit theorem, and the coding and transmission of information. The author includes many examples and exercises that illustrate how the theory can be applied, e.g. to information technology. Solutions are available by email. This book is suitable as a textbook for beginning students in mathematics, statistics, or computer science who have some knowledge of basic calculus.

Statistical Inference

Author: Helio S. Migon
Publisher: CRC Press
ISBN: 1439878803
Size: 53.95 MB
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A Balanced Treatment of Bayesian and Frequentist Inference Statistical Inference: An Integrated Approach, Second Edition presents an account of the Bayesian and frequentist approaches to statistical inference. Now with an additional author, this second edition places a more balanced emphasis on both perspectives than the first edition. New to the Second Edition New material on empirical Bayes and penalized likelihoods and their impact on regression models Expanded material on hypothesis testing, method of moments, bias correction, and hierarchical models More examples and exercises More comparison between the approaches, including their similarities and differences Designed for advanced undergraduate and graduate courses, the text thoroughly covers statistical inference without delving too deep into technical details. It compares the Bayesian and frequentist schools of thought and explores procedures that lie on the border between the two. Many examples illustrate the methods and models, and exercises are included at the end of each chapter.

Statistical Inference

Author: Murray Aitkin
Publisher: CRC Press
ISBN: 1420093444
Size: 79.96 MB
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Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct Bayesian counterparts of frequentist t-tests and other standard statistical methods for hypothesis testing. After an overview of the competing theories of statistical inference, the book introduces the Bayes/likelihood approach used throughout. It presents Bayesian versions of one- and two-sample t-tests, along with the corresponding normal variance tests. The author then thoroughly discusses the use of the multinomial model and noninformative Dirichlet priors in "model-free" or nonparametric Bayesian survey analysis, before covering normal regression and analysis of variance. In the chapter on binomial and multinomial data, he gives alternatives, based on Bayesian analyses, to current frequentist nonparametric methods. The text concludes with new goodness-of-fit methods for assessing parametric models and a discussion of two-level variance component models and finite mixtures. Emphasizing the principles of Bayesian inference and Bayesian model comparison, this book develops a unique methodology for solving challenging inference problems. It also includes a concise review of the various approaches to inference.

Regression And Anova

Author: Keith E. Muller
Publisher: SAS Institute
ISBN: 9781580258906
Size: 74.10 MB
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This book provides a thorough and integrated treatment of multiple regression and ANOVA. The information it contains has served as the basis for a graduate-level biostatistics class at the University of North Carolina at Chapel Hill. The book focuses on the general linear model (GLM) theory, stated in matrix terms, which provides a more compact, clear, and unified presentation of regression and ANOVA than do traditional sums of squares and scalar equations. The book offers a balanced treatment of regression and ANOVA, yet is very compact. Reflecting current computational practice, most sums of squares formulas and associated theory, especially in ANOVA, are not included. The text includes almost no proofs, despite the presence of a large number of basic theoretical results. Many numerical examples are provided and include both the SAS code and equivalent mathematical representation needed to produce the outputs that are presented. All exercises involve only real data, collected in the course of scientific research. The book is divided into sections covering the following topics: basic theory; multiple regression; model building and evaluation; ANOVA; and ANCOVA.

Operations Management An Integrated Approach 6th Edition

Author: R. Dan Reid
Publisher: Wiley Global Education
ISBN: 1118952553
Size: 54.35 MB
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In the 6th Edition of Operations Management, Dan Reid and Nada Sanders have strengthened their commitment to improve the teaching and learning experience in the introductory operations management course. The text provides a solid foundation of Operations Management with clear, guided instruction and a balance between quantitative and qualitative concepts. Through an integrated approach, the authors illustrate how all business students will interact with Operations Management in future careers.

Environmental Economics

Author: Philip E. Graves
Publisher: CRC Press
ISBN: 1466518022
Size: 15.64 MB
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Rigorous, yet written in a way that facilitates understanding of complex material, Environmental Economics: An Integrated Approach provides practical and working knowledge of how environmental policy analysis is developed. This is a true textbook, detailing the tools required to conduct that analysis and also discusses weaknesses in the existing methods, underlining areas for future improvement. This approach allows readers to get a sense of what is known and what is not known about environmental economics. The book discusses why we have environmental problems and how we would optimally react if we had perfect information about environmental benefits and costs. It then describes methods in use—and their flaws—to acquire the information necessary to enact environmental policy. The book starts with a categorization of goods types, concluding that environmental problems stem from non-excludable goods that are either rivalrous or non-rivalrous. The author introduces the Coase Theorem in the first chapter, then details how households and firms would behave when facing a zero price on pollution versus a price on pollution set equal to presumed known marginal damages. He connects the economic system with the environmental system by aggregating up from individual decisions to the aggregate market system and the aggregate environmental quality. But, of course, the information available is rarely perfect. Clarifying the information difficulties faced by households, firms, and policy makers, the author recognizes that there is both a knowledge gap and a communication gap. He then covers the methods policy makers employ in an attempt to gain sufficient insight into marginal benefits and marginal costs to properly set a marginal damage tax, properly limit emission rights, or properly provide public goods. The book then examines the nature of these methods and their likely bias, before concluding that surviving the next 50 to 100 years will lead to a world of ever-improving levels of economic and environmental goods—but the sobering qualifier is that without proper environmental policies there is a significant probability that our species will not be able to reach that desirable outcome.

Statistical Mechanics And The Physics Of Many Particle Model Systems

Author: Kuzemsky Alexander Leonidovich
Publisher: World Scientific
ISBN: 981314565X
Size: 37.91 MB
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The book is devoted to the study of the correlation effects in many-particle systems. It presents the advanced methods of quantum statistical mechanics (equilibrium and nonequilibrium), and shows their effectiveness and operational ability in applications to problems of quantum solid-state theory, quantum theory of magnetism and the kinetic theory. The book includes description of the fundamental concepts and techniques of analysis following the approach of N N Bogoliubov's school, including recent developments. It provides an overview that introduces the main notions of quantum many-particle physics with the emphasis on concepts and models. This book combines the features of textbook and research monograph. For many topics the aim is to start from the beginning and to guide the reader to the threshold of advanced researches. Many chapters include also additional information and discuss many complex research areas which are not often discussed in other places. The book is useful for established researchers to organize and present the advanced material disseminated in the literature. The book contains also an extensive bibliography. The book serves undergraduate, graduate and postgraduate students, as well as researchers who have had prior experience with the subject matter at a more elementary level or have used other many-particle techniques.

Epidemiological Research Methods

Author: Don McNeil
Publisher: John Wiley & Sons
ISBN: 9780471961963
Size: 51.89 MB
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The concepts of epidemiology, the science that uses statistical methods to investigate associations between risk factors and disease outcomes in human populations, are developed using examples involving real data from published studies. The relevant statistical methods are developed systematically to provide an integrated approach to observational and experimental studies. After covering basic measurement, study design, and study credibility issues, the author continues with basic statistical methods and techniques for adjusting risk estimates for confounders. Statistical models including logistic regression and the proportional hazards model for survival analysis are explained in detail in the following chapters, concluding with an explanation of the general methods for determining the sample size and power requirements for an epidemiological study. Taking advantage of the power, accessibility and user-friendliness of modern computer packages, the author uses a variety of interesting data sets and graphical displays to illustrate the methods. Epidemiological Research Methods will be of interest to students and research workers who need to learn and appreciate modern approaches to the subject. Without unnecessary emphasis on mathematics or theory, the book will enable the reader to gain a greater level of understanding of the underlying methods than is normally provided in books on epidemiology.

Statistics A Very Short Introduction

Author: David J. Hand
Publisher: OUP Oxford
ISBN: 0191578924
Size: 29.25 MB
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Modern statistics is very different from the dry and dusty discipline of the popular imagination. In its place is an exciting subject which uses deep theory and powerful software tools to shed light and enable understanding. And it sheds this light on all aspects of our lives, enabling astronomers to explore the origins of the universe, archaeologists to investigate ancient civilisations, governments to understand how to benefit and improve society, and businesses to learn how best to provide goods and services. Aimed at readers with no prior mathematical knowledge, this Very Short Introduction explores and explains how statistics work, and how we can decipher them. ABOUT THE SERIES: The Very Short Introductions series from Oxford University Press contains hundreds of titles in almost every subject area. These pocket-sized books are the perfect way to get ahead in a new subject quickly. Our expert authors combine facts, analysis, perspective, new ideas, and enthusiasm to make interesting and challenging topics highly readable.