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Author : Megan N. Shoji
Publisher :
ISBN 13 :
Total Pages : 59 pages
Book Rating : 4.:/5 (815 download)
Download or read book A Demonstration of Bayesian Statistical Inference in Education Research written by Megan N. Shoji and published by . This book was released on 2012 with total page 59 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gudmund R. Iversen
Publisher : SAGE
ISBN 13 : 9780803923287
Total Pages : 88 pages
Book Rating : 4.9/5 (232 download)
Download or read book Bayesian Statistical Inference written by Gudmund R. Iversen and published by SAGE. This book was released on 1984-11 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians now generally acknowledge the theorectical importance of Bayesian inference, if not its practical validity. According to Gudmund R. Iversen, one reason for the lag in applications is that empirical researchers have lacked a grounding in the methodology. His volume provides this introduction and serves as a companion to #4, Tests of Significance.
Author : Tonio Di Battista
Publisher : Springer
ISBN 13 : 3319440934
Total Pages : 222 pages
Book Rating : 4.3/5 (194 download)
Download or read book Topics on Methodological and Applied Statistical Inference written by Tonio Di Battista and published by Springer. This book was released on 2016-10-11 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together selected peer-reviewed contributions from various research fields in statistics, and highlights the diverse approaches and analyses related to real-life phenomena. Major topics covered in this volume include, but are not limited to, bayesian inference, likelihood approach, pseudo-likelihoods, regression, time series, and data analysis as well as applications in the life and social sciences. The software packages used in the papers are made available by the authors. This book is a result of the 47th Scientific Meeting of the Italian Statistical Society, held at the University of Cagliari, Italy, in 2014.
Author : Russell G. Almond
Publisher : Springer
ISBN 13 : 1493921258
Total Pages : 678 pages
Book Rating : 4.4/5 (939 download)
Download or read book Bayesian Networks in Educational Assessment written by Russell G. Almond and published by Springer. This book was released on 2015-03-10 with total page 678 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian inference networks, a synthesis of statistics and expert systems, have advanced reasoning under uncertainty in medicine, business, and social sciences. This innovative volume is the first comprehensive treatment exploring how they can be applied to design and analyze innovative educational assessments. Part I develops Bayes nets’ foundations in assessment, statistics, and graph theory, and works through the real-time updating algorithm. Part II addresses parametric forms for use with assessment, model-checking techniques, and estimation with the EM algorithm and Markov chain Monte Carlo (MCMC). A unique feature is the volume’s grounding in Evidence-Centered Design (ECD) framework for assessment design. This “design forward” approach enables designers to take full advantage of Bayes nets’ modularity and ability to model complex evidentiary relationships that arise from performance in interactive, technology-rich assessments such as simulations. Part III describes ECD, situates Bayes nets as an integral component of a principled design process, and illustrates the ideas with an in-depth look at the BioMass project: An interactive, standards-based, web-delivered demonstration assessment of science inquiry in genetics. This book is both a resource for professionals interested in assessment and advanced students. Its clear exposition, worked-through numerical examples, and demonstrations from real and didactic applications provide invaluable illustrations of how to use Bayes nets in educational assessment. Exercises follow each chapter, and the online companion site provides a glossary, data sets and problem setups, and links to computational resources.
Author : Donald L. Meyer
Publisher :
ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.3/5 (512 download)
Download or read book Bayesian Statistics written by Donald L. Meyer and published by . This book was released on 1970 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jeffrey M. Stanton
Publisher : Guilford Publications
ISBN 13 : 1462530281
Total Pages : 337 pages
Book Rating : 4.4/5 (625 download)
Download or read book Reasoning with Data written by Jeffrey M. Stanton and published by Guilford Publications. This book was released on 2017-04-28 with total page 337 pages. Available in PDF, EPUB and Kindle. Book excerpt: Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides step-by-step guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the open-source R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using real-data examples. The companion website provides annotated R code for the book's examples, in-class exercises, teaching notes, and slide decks. Pedagogical Features *Playful, conversational style and gradual approach; suitable for students without strong math backgrounds. *End-of-chapter exercises based on real data supplied in the free R package. *Technical explanation and equation/output boxes. *Appendices on how to install R and work with the sample datasets.
Author : Scott M. Lynch
Publisher : Springer Science & Business Media
ISBN 13 : 0387712658
Total Pages : 376 pages
Book Rating : 4.3/5 (877 download)
Download or read book Introduction to Applied Bayesian Statistics and Estimation for Social Scientists written by Scott M. Lynch and published by Springer Science & Business Media. This book was released on 2007-06-30 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.
Author : Gary L Rosner
Publisher : CRC Press
ISBN 13 : 1000353001
Total Pages : 564 pages
Book Rating : 4.0/5 (3 download)
Download or read book Bayesian Thinking in Biostatistics written by Gary L Rosner and published by CRC Press. This book was released on 2021-03-16 with total page 564 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for Bayesian Thinking in Biostatistics: "This thoroughly modern Bayesian book ...is a 'must have' as a textbook or a reference volume. Rosner, Laud and Johnson make the case for Bayesian approaches by melding clear exposition on methodology with serious attention to a broad array of illuminating applications. These are activated by excellent coverage of computing methods and provision of code. Their content on model assessment, robustness, data-analytic approaches and predictive assessments...are essential to valid practice. The numerous exercises and professional advice make the book ideal as a text for an intermediate-level course..." -Thomas Louis, Johns Hopkins University "The book introduces all the important topics that one would usually cover in a beginning graduate level class on Bayesian biostatistics. The careful introduction of the Bayesian viewpoint and the mechanics of implementing Bayesian inference in the early chapters makes it a complete self- contained introduction to Bayesian inference for biomedical problems....Another great feature for using this book as a textbook is the inclusion of extensive problem sets, going well beyond construed and simple problems. Many exercises consider real data and studies, providing very useful examples in addition to serving as problems." - Peter Mueller, University of Texas With a focus on incorporating sensible prior distributions and discussions on many recent developments in Bayesian methodologies, Bayesian Thinking in Biostatistics considers statistical issues in biomedical research. The book emphasizes greater collaboration between biostatisticians and biomedical researchers. The text includes an overview of Bayesian statistics, a discussion of many of the methods biostatisticians frequently use, such as rates and proportions, regression models, clinical trial design, and methods for evaluating diagnostic tests. Key Features Applies a Bayesian perspective to applications in biomedical science Highlights advances in clinical trial design Goes beyond standard statistical models in the book by introducing Bayesian nonparametric methods and illustrating their uses in data analysis Emphasizes estimation of biomedically relevant quantities and assessment of the uncertainty in this estimation Provides programs in the BUGS language, with variants for JAGS and Stan, that one can use or adapt for one's own research The intended audience includes graduate students in biostatistics, epidemiology, and biomedical researchers, in general Authors Gary L. Rosner is the Eli Kennerly Marshall, Jr., Professor of Oncology at the Johns Hopkins School of Medicine and Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health. Purushottam (Prakash) W. Laud is Professor in the Division of Biostatistics, and Director of the Biostatistics Shared Resource for the Cancer Center, at the Medical College of Wisconsin. Wesley O. Johnson is professor Emeritus in the Department of Statistics as the University of California, Irvine.
Author : James Berger
Publisher : CRC Press
ISBN 13 : 1003837646
Total Pages : 421 pages
Book Rating : 4.0/5 (38 download)
Download or read book Handbook of Bayesian, Fiducial, and Frequentist Inference written by James Berger and published by CRC Press. This book was released on 2024-02-26 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference. Key Features: Provides a comprehensive introduction to the key developments in the BFF schools of inference Gives an overview of modern inferential methods, allowing scientists in other fields to expand their knowledge Is accessible for readers with different perspectives and backgrounds
Author : William M. Bolstad
Publisher : John Wiley & Sons
ISBN 13 : 1118619218
Total Pages : 353 pages
Book Rating : 4.1/5 (186 download)
Download or read book Introduction to Bayesian Statistics written by William M. Bolstad and published by John Wiley & Sons. This book was released on 2013-06-05 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "I cannot think of a better book for teachers of introductory statistics who want a readable and pedagogically sound text to introduce Bayesian statistics." —Statistics in Medical Research "[This book] is written in a lucid conversational style, which is so rare in mathematical writings. It does an excellent job of presenting Bayesian statistics as a perfectly reasonable approach to elementary problems in statistics." —STATS: The Magazine for Students of Statistics, American Statistical Association "Bolstad offers clear explanations of every concept and method making the book accessible and valuable to undergraduate and graduate students alike." —Journal of Applied Statistics The use of Bayesian methods in applied statistical analysis has become increasingly popular, yet most introductory statistics texts continue to only present the subject using frequentist methods. Introduction to Bayesian Statistics, Second Edition focuses on Bayesian methods that can be used for inference, and it also addresses how these methods compare favorably with frequentist alternatives. Teaching statistics from the Bayesian perspective allows for direct probability statements about parameters, and this approach is now more relevant than ever due to computer programs that allow practitioners to work on problems that contain many parameters. This book uniquely covers the topics typically found in an introductory statistics book—but from a Bayesian perspective—giving readers an advantage as they enter fields where statistics is used. This Second Edition provides: Extended coverage of Poisson and Gamma distributions Two new chapters on Bayesian inference for Poisson observations and Bayesian inference for the standard deviation for normal observations A twenty-five percent increase in exercises with selected answers at the end of the book A calculus refresher appendix and a summary on the use of statistical tables New computer exercises that use R functions and Minitab® macros for Bayesian analysis and Monte Carlo simulations Introduction to Bayesian Statistics, Second Edition is an invaluable textbook for advanced undergraduate and graduate-level statistics courses as well as a practical reference for statisticians who require a working knowledge of Bayesian statistics.
Author : D. V. Lindley
Publisher : SIAM
ISBN 13 : 9781611970654
Total Pages : 88 pages
Book Rating : 4.9/5 (76 download)
Download or read book Bayesian Statistics, A Review written by D. V. Lindley and published by SIAM. This book was released on 1972-01-31 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: A study of those statistical ideas that use a probability distribution over parameter space. The first part describes the axiomatic basis in the concept of coherence and the implications of this for sampling theory statistics. The second part discusses the use of Bayesian ideas in many branches of statistics.
Author : Therese M. Donovan
Publisher : Oxford University Press
ISBN 13 : 0192578251
Total Pages : 432 pages
Book Rating : 4.1/5 (925 download)
Download or read book Bayesian Statistics for Beginners written by Therese M. Donovan and published by Oxford University Press. This book was released on 2019-05-23 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian statistics is currently undergoing something of a renaissance. At its heart is a method of statistical inference in which Bayes' theorem is used to update the probability for a hypothesis as more evidence or information becomes available. It is an approach that is ideally suited to making initial assessments based on incomplete or imperfect information; as that information is gathered and disseminated, the Bayesian approach corrects or replaces the assumptions and alters its decision-making accordingly to generate a new set of probabilities. As new data/evidence becomes available the probability for a particular hypothesis can therefore be steadily refined and revised. It is very well-suited to the scientific method in general and is widely used across the social, biological, medical, and physical sciences. Key to this book's novel and informal perspective is its unique pedagogy, a question and answer approach that utilizes accessible language, humor, plentiful illustrations, and frequent reference to on-line resources. Bayesian Statistics for Beginners is an introductory textbook suitable for senior undergraduate and graduate students, professional researchers, and practitioners seeking to improve their understanding of the Bayesian statistical techniques they routinely use for data analysis in the life and medical sciences, psychology, public health, business, and other fields.
Author : Ming-Hui Chen
Publisher : Springer Science & Business Media
ISBN 13 : 1441969446
Total Pages : 631 pages
Book Rating : 4.4/5 (419 download)
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.
Author : Andrew Gelman
Publisher : Oxford University Press
ISBN 13 : 0191088641
Total Pages : 465 pages
Book Rating : 4.1/5 (91 download)
Download or read book Teaching Statistics written by Andrew Gelman and published by Oxford University Press. This book was released on 2017-08-03 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation. Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'-- with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication. Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided. Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.
Author : Henry Rouanet
Publisher : Peter Lang Publishing
ISBN 13 :
Total Pages : 300 pages
Book Rating : 4.:/5 (321 download)
Download or read book New Ways in Statistical Methodology written by Henry Rouanet and published by Peter Lang Publishing. This book was released on 1998 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents work developed within the Mathematics and Psychology Group of the French National Center for Scientific Research. New trends in statistical methodology are presented, along with an analysis of researchers' attitudes toward statistical inference, and concrete proposals for improving statistical practice. Discussion encompasses combinatorial inference, fiducial Bayesian inference, Bayesian inference for categorized data, and geometric data. Of interest to researchers, statisticians, and statistics users in behavioral and social sciences. Rouanet is director of research at the French National Center for Scientific Research at the University Rene Descartes. Annotation copyrighted by Book News, Inc., Portland, OR.
Author : David Kaplan
Publisher : Guilford Publications
ISBN 13 : 146251667X
Total Pages : 338 pages
Book Rating : 4.4/5 (625 download)
Download or read book Bayesian Statistics for the Social Sciences written by David Kaplan and published by Guilford Publications. This book was released on 2014-07-16 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book has been replaced by Bayesian Statistics for the Social Sciences, Second Edition, ISBN 978-1-4625-5354-9.
Author : David Kaplan
Publisher : Guilford Publications
ISBN 13 : 1462553540
Total Pages : 274 pages
Book Rating : 4.4/5 (625 download)
Download or read book Bayesian Statistics for the Social Sciences written by David Kaplan and published by Guilford Publications. This book was released on 2023-11-10 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Since the publication of the first edition, Bayesian statistics is, arguably, still not the norm in the formal quantitative methods training of social scientists. Typically, the only introduction that a student might have to Bayesian ideas is a brief overview of Bayes' theorem while studying probability in an introductory statistics class. This is not surprising. First, until relatively recently, it was not feasible to conduct statistical modeling from a Bayesian perspective owing to its complexity and lack of available software. Second, Bayesian statistics represents a powerful alternative to frequentist (conventional) statistics and, therefore, can be controversial, especially in the context of null hypothesis significance testing. However, over the last 20 years, or so, considerably progress has been made in the development and application of complex Bayesian statistical methods, due mostly to developments and availability of proprietary and open-source statistical software tools. And, although Bayesian statistics is not quite yet an integral part of the quantitative training of social scientists, there has been increasing interest in the application of Bayesian methods, and it is not unreasonable to say that in terms of theoretical developments and substantive applications, Bayesian statistics has arrived. Because of extensive developments in Bayesian theory and computation since the publication of the first edition of this book, there was a pressing need for a thorough update of the material to reflect new developments in Bayesian methodology and software. The basic foundations of Bayesian statistics remain more or less the same, but this second edition encompasses many new extensions"--
