Doing Bayesian Data Analysis
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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
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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 : 2010-11-25
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 2010-11-25 with Mathematics categories.
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and 'rusty' calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods. - 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:
Release Date : 2010
Doing Bayesian Data Analysis 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 2010 with Mathematics categories.
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and 'rusty' calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs. The textbook bridges the students from their undergraduate training into modern Bayesian methods.-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 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.
Bayesian Data Analysis Of Gambling Preferences
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Author : Dirk Wendt
language : en
Publisher:
Release Date :
Bayesian Data Analysis Of Gambling Preferences written by Dirk Wendt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Some Criticisms Of The General Models Used In Decision Making Experiments
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Author : Dirk Wendt
language : en
Publisher:
Release Date : 1973
Some Criticisms Of The General Models Used In Decision Making Experiments written by Dirk Wendt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1973 with categories.
Bayesian Data Analysis
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Author : Andrew Gelman
language : en
Publisher: CRC Press
Release Date : 2013-11-27
Bayesian Data Analysis written by Andrew Gelman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-27 with Mathematics categories.
Winner of the 2016 De Groot Prize from the International Society for Bayesian AnalysisNow in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied
Drug Information A Guide For Pharmacists 7th Edition
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Author : Patrick M. Malone
language : en
Publisher: McGraw Hill Professional
Release Date : 2021-11-19
Drug Information A Guide For Pharmacists 7th Edition written by Patrick M. Malone and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-19 with Medical categories.
Everything pharmacists and pharmacy students need to know about drug information management A Doody's Core Title for 2023! Drug Information: A Guide for Pharmacists provides you with the tools you need to to research, interpret, evaluate, collate, and disseminate drug information in the most effective and efficient manner possible. This trusted resource addresses essential topics such as formulating an effective response and recommendations for information, evaluation of drug literature, the application of statistical analysis in the biomedical sciences, medications and patient safety, investigational drugs, and more. This updated seventh edition also addresses other important issues such as the legal and ethical considerations of providing information, how to respond to requests for information, and how to determine what information should be made available.
Drug Information A Guide For Pharmacists Sixth Edition
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Author : Patrick M. Malone
language : en
Publisher: McGraw Hill Professional
Release Date : 2017-12-13
Drug Information A Guide For Pharmacists Sixth Edition written by Patrick M. Malone and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-13 with Medical categories.
The guide pharmacists and students turn to first for cutting-edge coverage of drug information A Doody’s Core Title for 2021! The goal of Drug Information: A Guide for Pharmacists, Sixth Edition is to teach students and practitioners how to effectively research, interpret, evaluate, collate, and disseminate drug information in the most efficient and effective manner possible. Updated to reflect the realities of today’s practice, the book also addresses important issues such as the legal and ethical considerations of providing drug information. Drug Information: A Guide for Pharmacists begins by introducing the concept of drug information, including its history, and provides details on the various places drug information specialists may find employment. This is followed by information on how to answer a question, from the process of gathering necessary background information through determining the actual informational need, to answering the question. The chapter on drug information resources includes descriptions of the most commonly used references and contains new information on apps available to practitioners. As with past editions, practical examples are also provided. The Sixth Edition has been updated throughout, with chapters from previous editions rearranged to make the subject flow better. This edition is also enhanced by the addition of new chapters on journal clubs and counterfeit drugs/drug shortages. In addition, coverage of Policy Development, Project Design and Implementation has been greatly expanded.