Doing Bayesian Data Analysis 2nd Edition
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Doing Bayesian Data Analysis
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Author : John K. Kruschke
language : en
Publisher: Elsevier
Release Date : 2011
Doing Bayesian Data Analysis written by John K. Kruschke and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Mathematics categories.
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis obtainable to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS provides an accessible approach to Bayesian data analysis, as material is explained clearly with concrete examples. The book begins with the basics, including essential concepts of probability and random sampling, and gradually progresses to advanced hierarchical modeling methods for realistic data. The text delivers comprehensive coverage of all scenarios addressed by non-Bayesian textbooks--t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). This book is intended for first year graduate students or advanced undergraduates. It provides a bridge between undergraduate training and modern Bayesian methods for data analysis, which is becoming the accepted research standard. Prerequisite is knowledge of algebra and basic calculus. Free software now includes programs in JAGS, which runs on Macintosh, Linux, and Windows. Author website: http://www.indiana.edu/~kruschke/DoingBayesianDataAnalysis/ -Accessible, including the basics of essential concepts of probability and random sampling -Examples with R programming language and BUGS software -Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). -Coverage of experiment planning -R and BUGS computer programming code on website -Exercises have explicit purposes and guidelines for accomplishment
Doing Bayesian Data Analysis
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Author : John Kruschke
language : en
Publisher: Academic Press
Release Date : 2014-11-11
Doing Bayesian Data Analysis written by John Kruschke and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-11 with Mathematics categories.
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes' rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business. - Accessible, including the basics of essential concepts of probability and random sampling - Examples with R programming language and JAGS software - Comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) - Coverage of experiment planning - R and JAGS computer programming code on website - Exercises have explicit purposes and guidelines for accomplishment - Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs
Doing Bayesian Data Analysis 2nd Edition
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Author : John Kruschke
language : en
Publisher:
Release Date : 2014
Doing Bayesian Data Analysis 2nd Edition written by John Kruschke and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Mathematics categories.
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular, there are now compact high-level scripts that make it easy to run the programs on your own data sets. The book is divided into three parts and begins with the basics: models, probability, Bayes' rule, and the R programming language. The discussion then moves to the fundamentals applied to inferring a binomial probability, before concluding with chapters on the generalized linear model. Topics include metric-predicted variable on one or two groups; metric-predicted variable with one metric predictor; metric-predicted variable with multiple metric predictors; metric-predicted variable with one nominal predictor; and metric-predicted variable with multiple nominal predictors. The exercises found in the text have explicit purposes and guidelines for accomplishment. This book is intended for first-year graduate students or advanced undergraduates in statistics, data analysis, psychology, cognitive science, social sciences, clinical sciences, and consumer sciences in business. Accessible, including the basics of essential concepts of probability and random sampling Examples with R programming language and JAGS software Comprehensive coverage of all scenarios addressed by non-Bayesian textbooks: t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis) Coverage of experiment planning R and JAGS computer programming code on website Exercises have explicit purposes and guidelines for accomplishment Provides step-by-step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs.
Football Analytics With Python R
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Author : Eric A. Eager
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-08-15
Football Analytics With Python R written by Eric A. Eager and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-15 with Mathematics categories.
Baseball is not the only sport to use "moneyball." American football fans, teams, and gamblers are increasingly using data to gain an edge against the competition. Professional and college teams use data to help select players and identify team needs. Fans use data to guide fantasy team picks and strategies. Sports bettors and fantasy football players are using data to help inform decision making. This concise book provides a clear introduction to using statistical models to analyze football data. Whether your goal is to produce a winning team, dominate your fantasy football league, qualify for an entry-level football analyst position, or simply learn R and Python using fun example cases, this book is your starting place. You'll learn how to: Apply basic statistical concepts to football datasets Describe football data with quantitative methods Create efficient workflows that offer reproducible results Use data science skills such as web scraping, manipulating data, and plotting data Implement statistical models for football data Link data summaries and model outputs to create reports or presentations using tools such as R Markdown and R Shiny And more
Understanding Probability
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Author : Eshwar Sekhon
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Understanding Probability written by Eshwar Sekhon and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
"Understanding Probability" is an essential guide for students, researchers, and professionals to master the principles and diverse applications of probability theory. We meticulously explore core concepts like sample spaces, events, and probability distributions, and delve into advanced areas such as Bayesian inference, stochastic processes, and decision theory. Written for clarity, each chapter provides insightful explanations supported by real-world examples and practical applications. Our book spans multiple disciplines, including statistics, machine learning, finance, engineering, and operations research, making it a valuable resource for readers from various backgrounds. Numerous exercises and problems reinforce learning and equip readers to apply probability theory to real-world scenarios. "Understanding Probability" is an invaluable resource that deepens your understanding of probability and its crucial role in navigating uncertainties in the world around us.
Advances In Evidence Based Policing
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Author : Johannes Knutsson
language : en
Publisher: Taylor & Francis
Release Date : 2017-04-21
Advances In Evidence Based Policing written by Johannes Knutsson and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-21 with Social Science categories.
The evidence-based policing (EBP) movement has intensified in many countries around the world in recent years, resulting in a proliferation of policies and infrastructure to support such a transformation. This movement has come to be associated with particular methods of evaluation and systematic review, which have been drawn from what is assumed to prevail in medicine. Given the credibility EBP is currently enjoying with both practitioners and government, it is timely to subject its underpinning logic to thoughtful scrutiny. This involves deliberating upon the meaning of evidence and what different models of knowledge accumulation and research methods have to offer in realising the aims of EBP. The communication and presentation of evidence to practitioner audiences is another important aspect of EBP, as are collaborative efforts to ‘co-produce’ new knowledge on police practice. This is the first book that takes a kaleidoscopic approach to depict what EBP presently is and how it could develop. The chapters individually and collectively challenge the underlying logic to the mainstream EBP position, and the book concludes with an agenda for a more inclusive conceptualisation of evidence and EBP for the future. It is aimed at students and academics who are interested in being part of this movement, as well as policymakers and practitioners interested in integrating EBP principles into their practices.
Introduction To Bayesian Estimation And Copula Models Of Dependence
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Author : Arkady Shemyakin
language : en
Publisher: John Wiley & Sons
Release Date : 2017-03-03
Introduction To Bayesian Estimation And Copula Models Of Dependence written by Arkady Shemyakin and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-03-03 with Mathematics categories.
Presents an introduction to Bayesian statistics, presents an emphasis on Bayesian methods (prior and posterior), Bayes estimation, prediction, MCMC,Bayesian regression, and Bayesian analysis of statistical modelsof dependence, and features a focus on copulas for risk management Introduction to Bayesian Estimation and Copula Models of Dependence emphasizes the applications of Bayesian analysis to copula modeling and equips readers with the tools needed to implement the procedures of Bayesian estimation in copula models of dependence. This book is structured in two parts: the first four chapters serve as a general introduction to Bayesian statistics with a clear emphasis on parametric estimation and the following four chapters stress statistical models of dependence with a focus of copulas. A review of the main concepts is discussed along with the basics of Bayesian statistics including prior information and experimental data, prior and posterior distributions, with an emphasis on Bayesian parametric estimation. The basic mathematical background of both Markov chains and Monte Carlo integration and simulation is also provided. The authors discuss statistical models of dependence with a focus on copulas and present a brief survey of pre-copula dependence models. The main definitions and notations of copula models are summarized followed by discussions of real-world cases that address particular risk management problems. In addition, this book includes: • Practical examples of copulas in use including within the Basel Accord II documents that regulate the world banking system as well as examples of Bayesian methods within current FDA recommendations • Step-by-step procedures of multivariate data analysis and copula modeling, allowing readers to gain insight for their own applied research and studies • Separate reference lists within each chapter and end-of-the-chapter exercises within Chapters 2 through 8 • A companion website containing appendices: data files and demo files in Microsoft® Office Excel®, basic code in R, and selected exercise solutions Introduction to Bayesian Estimation and Copula Models of Dependence is a reference and resource for statisticians who need to learn formal Bayesian analysis as well as professionals within analytical and risk management departments of banks and insurance companies who are involved in quantitative analysis and forecasting. This book can also be used as a textbook for upper-undergraduate and graduate-level courses in Bayesian statistics and analysis. ARKADY SHEMYAKIN, PhD, is Professor in the Department of Mathematics and Director of the Statistics Program at the University of St. Thomas. A member of the American Statistical Association and the International Society for Bayesian Analysis, Dr. Shemyakin's research interests include informationtheory, Bayesian methods of parametric estimation, and copula models in actuarial mathematics, finance, and engineering. ALEXANDER KNIAZEV, PhD, is Associate Professor and Head of the Department of Mathematics at Astrakhan State University in Russia. Dr. Kniazev's research interests include representation theory of Lie algebras and finite groups, mathematical statistics, econometrics, and financial mathematics.
The Sage Encyclopedia Of Industrial And Organizational Psychology
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Author : Steven G. Rogelberg
language : en
Publisher: SAGE Publications
Release Date : 2016-09-27
The Sage Encyclopedia Of Industrial And Organizational Psychology written by Steven G. Rogelberg and has been published by SAGE Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-27 with Psychology categories.
The well-received first edition of the Encyclopedia of Industrial and Organizational Psychology (2007, 2 vols) established itself in the academic library market as a landmark reference that presents a thorough overview of this cross-disciplinary field for students, researchers, and professionals in the areas of psychology, business, management, and human resources. Nearly ten years later, SAGE presents a thorough revision that both updates current entries and expands the overall coverage, adding approximately 200 new articles, expanding from two volumes to four. Examining key themes and topics from within this dynamic and expanding field of psychology, this work offers a truly cross-cultural and global perspective.
Advanced Research Methods For The Social And Behavioral Sciences
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Author : John E. Edlund
language : en
Publisher: Cambridge University Press
Release Date : 2019-03-14
Advanced Research Methods For The Social And Behavioral Sciences written by John E. Edlund and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-14 with Psychology categories.
Written by an interdisciplinary team of global experts, this book is an invaluable tool for anyone learning about research methods.
New Methods In Cognitive Psychology
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Author : Daniel Spieler
language : en
Publisher: Routledge
Release Date : 2019-10-28
New Methods In Cognitive Psychology written by Daniel Spieler and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-28 with Psychology categories.
This book provides an overview of cutting-edge methods currently being used in cognitive psychology, which are likely to appear with increasing frequency in coming years. Once built around univariate parametric statistics, cognitive psychology courses now seem deficient without some contact with methods for signal processing, spatial statistics, and machine learning. There are also important changes in analyses of behavioral data (e.g., hierarchical modeling and Bayesian inference) and there is the obvious change wrought by the advancement of functional imaging. This book begins by discussing the evidence of this rapid change, for example the movement between using traditional analyses of variance to multi-level mixed models, in psycholinguistics. It then goes on to discuss the methods for analyses of physiological measurements, and how these methods provide insights into cognitive processing. New Methods in Cognitive Psychology provides senior undergraduates, graduates and researchers with cutting-edge overviews of new and emerging topics, and the very latest in theory and research for the more established topics.