Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists

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Publisher : John Wiley & Sons
ISBN 13 : 0470185074
Total Pages : 418 pages
Book Rating : 4.4/5 (71 download)

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Book Synopsis Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by : Howard B. Stauffer

Download or read book Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists written by Howard B. Stauffer and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategies—the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DIC—to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences.

Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B.

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Publisher : Cram101
ISBN 13 : 9781478482710
Total Pages : 114 pages
Book Rating : 4.4/5 (827 download)

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Book Synopsis Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B. by : Cram101 Textbook Reviews

Download or read book Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B. written by Cram101 Textbook Reviews and published by Cram101. This book was released on 2013-05 with total page 114 pages. Available in PDF, EPUB and Kindle. Book excerpt: Never HIGHLIGHT a Book Again Virtually all testable terms, concepts, persons, places, and events are included. Cram101 Textbook Outlines gives all of the outlines, highlights, notes for your textbook with optional online practice tests. Only Cram101 Outlines are Textbook Specific. Cram101 is NOT the Textbook. Accompanys: 9780521673761

Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B., ISBN 9780470

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Publisher : Academic Internet Pub Incorporated
ISBN 13 : 9781619052260
Total Pages : 152 pages
Book Rating : 4.0/5 (522 download)

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Book Synopsis Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B., ISBN 9780470 by : Cram101 Textbook Reviews

Download or read book Studyguide for Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists by Stauffer, Howard B., ISBN 9780470 written by Cram101 Textbook Reviews and published by Academic Internet Pub Incorporated. This book was released on 2012-08 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Never HIGHLIGHT a Book Again! Virtually all of the testable terms, concepts, persons, places, and events from the textbook are included. Cram101 Just the FACTS101 studyguides give all of the outlines, highlights, notes, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanys: 9780470165041 .

Introduction to Bayesian Methods in Ecology and Natural Resources

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Publisher : Springer Nature
ISBN 13 : 303060750X
Total Pages : 188 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Introduction to Bayesian Methods in Ecology and Natural Resources by : Edwin J. Green

Download or read book Introduction to Bayesian Methods in Ecology and Natural Resources written by Edwin J. Green and published by Springer Nature. This book was released on 2020-11-26 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management. Bayesian analysis has undergone a remarkable transformation since the early 1990s. Widespread adoption of Markov chain Monte Carlo techniques has made the Bayesian paradigm the viable alternative to classical statistical procedures for scientific inference. The Bayesian approach has a number of desirable qualities, three chief ones being: i) the mathematical procedure is always the same, allowing the analyst to concentrate on the scientific aspects of the problem; ii) historical information is readily used, when appropriate; and iii) hierarchical models are readily accommodated. This monograph contains numerous worked examples and the requisite computer programs. The latter are easily modified to meet new situations. A primer on probability distributions is also included because these form the basis of Bayesian inference. Researchers and graduate students in Ecology and Natural Resource Management will find this book a valuable reference.

A Handbook of Basic Statistical Analyses using SPSS

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Publisher : Bootstrap Resources
ISBN 13 : 9671404111
Total Pages : 282 pages
Book Rating : 4.6/5 (714 download)

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Book Synopsis A Handbook of Basic Statistical Analyses using SPSS by : Mohammad Nasir bin Abdullah

Download or read book A Handbook of Basic Statistical Analyses using SPSS written by Mohammad Nasir bin Abdullah and published by Bootstrap Resources. This book was released on 2017-07-01 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This well respected text is designed for the first course in statistics and SPSS taken by students majoring in Business, Health, and Medicine. The text offers a balanced presentation of applications and theory. The authors take care to develop the theoretical foundations for the statistical methods presented at a level that is accessible to students with no statistical background. The examples in this book were chosen specifically for students in business, health, and medicine which include opportunities for real data analysis

Bayesian Models

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Publisher : Princeton University Press
ISBN 13 : 0691159289
Total Pages : 314 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Bayesian Models by : N. Thompson Hobbs

Download or read book Bayesian Models written by N. Thompson Hobbs and published by Princeton University Press. This book was released on 2015-08-04 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models

Janus-Faced Probability

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Publisher : Springer
ISBN 13 : 3319048619
Total Pages : 150 pages
Book Rating : 4.3/5 (19 download)

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Book Synopsis Janus-Faced Probability by : Paolo Rocchi

Download or read book Janus-Faced Probability written by Paolo Rocchi and published by Springer. This book was released on 2014-04-25 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: The problem of probability interpretation was long overlooked before exploding in the 20th century, when the frequentist and subjectivist schools formalized two conflicting conceptions of probability. Beyond the radical followers of the two schools, a circle of pluralist thinkers tends to reconcile the opposing concepts. The author uses two theorems in order to prove that the various interpretations of probability do come into opposition and can be used in different contexts. The goal here is to clarify the multi fold nature of probability by means of a purely mathematical approach and to show how philosophical arguments can only serve to deepen actual intellectual contrasts. The book can be considered as one of the most important contributions in the analysis of probability interpretation in the last 10-15 years.

Agent-Based and Individual-Based Modeling

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Publisher : Princeton University Press
ISBN 13 : 0691190836
Total Pages : 358 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Agent-Based and Individual-Based Modeling by : Steven F. Railsback

Download or read book Agent-Based and Individual-Based Modeling written by Steven F. Railsback and published by Princeton University Press. This book was released on 2019-03-26 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential textbook on agent-based modeling—now fully updated and expanded Agent-Based and Individual-Based Modeling has become the standard textbook on the subject for classroom use and self-instruction. Drawing on the latest version of NetLogo and fully updated with new examples, exercises, and an enhanced text for easier comprehension, this is the essential resource for anyone seeking to understand how the dynamics of biological, social, and other complex systems arise from the characteristics of the agents that make up these systems. Steven Railsback and Volker Grimm lead students stepwise through the processes of designing, programming, documenting, and doing scientific research with agent-based models, focusing on the adaptive behaviors that make these models necessary. They cover the fundamentals of modeling and model analysis, introduce key modeling concepts, and demonstrate how to implement them using NetLogo. They also address pattern-oriented modeling, an invaluable strategy for modeling real-world problems and developing theory. This accessible and authoritative book focuses on modeling as a tool for understanding real complex systems. It explains how to pose a specific question, use observations from actual systems to design models, write and test software, and more. A hands-on introduction that guides students from conceptual design to computer implementation to analysis Filled with new examples and exercises and compatible with the latest version of NetLogo Ideal for students and researchers across the natural and social sciences Written by two leading practitioners Supported by extensive instructional materials at www.railsback-grimm-abm-book.com

Modeling Populations of Adaptive Individuals

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Publisher : Princeton University Press
ISBN 13 : 0691180490
Total Pages : 195 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Modeling Populations of Adaptive Individuals by : Steven F. Railsback

Download or read book Modeling Populations of Adaptive Individuals written by Steven F. Railsback and published by Princeton University Press. This book was released on 2020-05-19 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book offers a new theory for modeling how organisms make tradeoff decisions and how these decisions affect both individuals and populations. Tradeoff decisions (or behaviors) are those that are optimize survival and include behaviors like foraging and reproduction. Existing theories have not painted a complete picture of tradeoff decisions because they only observe how the decisions of an individual affect them rather than how individuals impact, and are impacted by, the behavior of their communities. The authors' theory-which they call state and prediction based theory-uses individual-based models since these models show the complex ways that organisms relate to their environment. The authors' broader approach, one that integrates behavior and population dynamics, allows ecologists to see how individuals make adaptive tradeoff decisions. In simpler terms, this theory does not assume, as the previous models do, that future conditions are fixed, known, and unaffected by the behavior of others. Instead, the authors assume individuals make decisions like people do, which is by forecasting future conditions, using approximation to make good decisions, and updating their choices as conditions change"--

The Subjectivity of Scientists and the Bayesian Approach

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Publisher : John Wiley & Sons
ISBN 13 :
Total Pages : 304 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis The Subjectivity of Scientists and the Bayesian Approach by : S. James Press

Download or read book The Subjectivity of Scientists and the Bayesian Approach written by S. James Press and published by John Wiley & Sons. This book was released on 2001-04-16 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comparing and contrasting the reality of subjectivity in the work of history's great scientists and the modern Bayesian approach to statistical analysis Scientists and researchers are taught to analyze their data from an objective point of view, allowing the data to speak for themselves rather than assigning them meaning based on expectations or opinions. But scientists have never behaved fully objectively. Throughout history, some of our greatest scientific minds have relied on intuition, hunches, and personal beliefs to make sense of empirical data-and these subjective influences have often aided in humanity's greatest scientific achievements. The authors argue that subjectivity has not only played a significant role in the advancement of science, but that science will advance more rapidly if the modern methods of Bayesian statistical analysis replace some of the classical twentieth-century methods that have traditionally been taught. To accomplish this goal, the authors examine the lives and work of history's great scientists and show that even the most successful have sometimes misrepresented findings or been influenced by their own preconceived notions of religion, metaphysics, and the occult, or the personal beliefs of their mentors. Contrary to popular belief, our greatest scientific thinkers approached their data with a combination of subjectivity and empiricism, and thus informally achieved what is more formally accomplished by the modern Bayesian approach to data analysis. Yet we are still taught that science is purely objective. This innovative book dispels that myth using historical accounts and biographical sketches of more than a dozen great scientists, including Aristotle, Galileo Galilei, Johannes Kepler, William Harvey, Sir Isaac Newton, Antoine Levoisier, Alexander von Humboldt, Michael Faraday, Charles Darwin, Louis Pasteur, Gregor Mendel, Sigmund Freud, Marie Curie, Robert Millikan, Albert Einstein, Sir Cyril Burt, and Margaret Mead. Also included is a detailed treatment of the modern Bayesian approach to data analysis. Up-to-date references to the Bayesian theoretical and applied literature, as well as reference lists of the primary sources of the principal works of all the scientists discussed, round out this comprehensive treatment of the subject. Readers will benefit from this cogent and enlightening view of the history of subjectivity in science and the authors' alternative vision of how the Bayesian approach should be used to further the cause of science and learning well into the twenty-first century.

Good Statistical Practice for Natural Resources Research

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Publisher : CABI
ISBN 13 : 0851997228
Total Pages : 410 pages
Book Rating : 4.8/5 (519 download)

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Book Synopsis Good Statistical Practice for Natural Resources Research by : Roger Stern

Download or read book Good Statistical Practice for Natural Resources Research written by Roger Stern and published by CABI. This book was released on 2004 with total page 410 pages. Available in PDF, EPUB and Kindle. Book excerpt: Part 1: Introduction Chapter 1: What is Natural Resources Research? Chapter 2: At Least Read This. Chapter 3: Sidetracks Part 2: Planning Chapter 4: Introduction to Research Planning Chapter 5: Concepts Underlying Experiments Chapter 6: Sampling Concepts Chapter 7: Surveys and Studies of Human Subjects Chapter 8: Surveying Land and Natural Populations Chapter 9: Planning Effective Experiments Part 3: Data Management Chapter 10: Data Management Issues and Problems Chapter 11: Use of Spreadsheet Packages Chapter 12: The Role of a Database Package Chapter 13: Developing a Data Management Strategy Chapter 14: Use of Statistical Software Part 4: Analysis Chapter 15: Analysis - Aims and Approaches Chapter 16: The DIY Toolbox - General Ideas 16.1 Opening the Toolbox 221 Chapter 17: Analysis of Survey Data Chapter 18: Analysis of Experimental Data Chapter 19: General Linear Models Chapter 20: The Craftsman's Toolbox Chapter 21: Informative Presentation of Tables, Graphs and Statistics Part 5: Where Next? Chapter 22: Current Trends and their Implications for Good Practice Chapter 23: Resources and Further Reading.

Frontiers of Statistical Decision Making and Bayesian Analysis

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Publisher : Springer Science & Business Media
ISBN 13 : 1441969446
Total Pages : 631 pages
Book Rating : 4.4/5 (419 download)

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Book Synopsis Frontiers of Statistical Decision Making and Bayesian Analysis by : Ming-Hui Chen

Download or read book Frontiers of Statistical Decision Making and Bayesian Analysis written by Ming-Hui Chen and published by Springer Science & Business Media. This book was released on 2010-07-24 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in Bayesian analysis and statistical decision theory is rapidly expanding and diversifying, making it increasingly more difficult for any single researcher to stay up to date on all current research frontiers. This book provides a review of current research challenges and opportunities. While the book can not exhaustively cover all current research areas, it does include some exemplary discussion of most research frontiers. Topics include objective Bayesian inference, shrinkage estimation and other decision based estimation, model selection and testing, nonparametric Bayes, the interface of Bayesian and frequentist inference, data mining and machine learning, methods for categorical and spatio-temporal data analysis and posterior simulation methods. Several major application areas are covered: computer models, Bayesian clinical trial design, epidemiology, phylogenetics, bioinformatics, climate modeling and applications in political science, finance and marketing. As a review of current research in Bayesian analysis the book presents a balance between theory and applications. The lack of a clear demarcation between theoretical and applied research is a reflection of the highly interdisciplinary and often applied nature of research in Bayesian statistics. The book is intended as an update for researchers in Bayesian statistics, including non-statisticians who make use of Bayesian inference to address substantive research questions in other fields. It would also be useful for graduate students and research scholars in statistics or biostatistics who wish to acquaint themselves with current research frontiers.

Bayesian Statistical Methods

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Publisher : CRC Press
ISBN 13 : 0429510918
Total Pages : 288 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Bayesian Statistical Methods by : Brian J. Reich

Download or read book Bayesian Statistical Methods written by Brian J. Reich and published by CRC Press. This book was released on 2019-04-12 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis. This book focuses on Bayesian methods applied routinely in practice including multiple linear regression, mixed effects models and generalized linear models (GLM). The authors include many examples with complete R code and comparisons with analogous frequentist procedures. In addition to the basic concepts of Bayesian inferential methods, the book covers many general topics: Advice on selecting prior distributions Computational methods including Markov chain Monte Carlo (MCMC) Model-comparison and goodness-of-fit measures, including sensitivity to priors Frequentist properties of Bayesian methods Case studies covering advanced topics illustrate the flexibility of the Bayesian approach: Semiparametric regression Handling of missing data using predictive distributions Priors for high-dimensional regression models Computational techniques for large datasets Spatial data analysis The advanced topics are presented with sufficient conceptual depth that the reader will be able to carry out such analysis and argue the relative merits of Bayesian and classical methods. A repository of R code, motivating data sets, and complete data analyses are available on the book’s website. Brian J. Reich, Associate Professor of Statistics at North Carolina State University, is currently the editor-in-chief of the Journal of Agricultural, Biological, and Environmental Statistics and was awarded the LeRoy & Elva Martin Teaching Award. Sujit K. Ghosh, Professor of Statistics at North Carolina State University, has over 22 years of research and teaching experience in conducting Bayesian analyses, received the Cavell Brownie mentoring award, and served as the Deputy Director at the Statistical and Applied Mathematical Sciences Institute.

Mathematical Reviews

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Publisher :
ISBN 13 :
Total Pages : 984 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Mathematical Reviews by :

Download or read book Mathematical Reviews written by and published by . This book was released on 2008 with total page 984 pages. Available in PDF, EPUB and Kindle. Book excerpt:

AMSTAT News

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Publisher :
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis AMSTAT News by : American Statistical Association

Download or read book AMSTAT News written by American Statistical Association and published by . This book was released on 2008 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Bayesian Statistics for Experimental Scientists

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Publisher : MIT Press
ISBN 13 : 0262360705
Total Pages : 473 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Bayesian Statistics for Experimental Scientists by : Richard A. Chechile

Download or read book Bayesian Statistics for Experimental Scientists written by Richard A. Chechile and published by MIT Press. This book was released on 2020-09-08 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis. This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book's premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics.

Journal of the American Statistical Association

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Publisher :
ISBN 13 :
Total Pages : 898 pages
Book Rating : 4.:/5 ( download)

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Book Synopsis Journal of the American Statistical Association by :

Download or read book Journal of the American Statistical Association written by and published by . This book was released on 2009 with total page 898 pages. Available in PDF, EPUB and Kindle. Book excerpt: