MARC details
| 000 -LEADER |
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| fixed length control field |
02736nam a2200241Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20240820120648.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
240814s2014 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9780124058880 |
| 040 ## - CATALOGING SOURCE |
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| Transcribing agency |
SIU |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
279.5 KRU 2014 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Kruschke, John K. |
| 245 ## - TITLE STATEMENT |
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| Title |
Doing Bayesian Data Analysis: |
| Remainder of title |
A Tutorial with R, JAGS, and Stan |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
2nd edition |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. |
|---|
| Place of publication, distribution, etc. |
United States |
| Name of publisher, distributor, etc. |
Academic Press |
| Date of publication, distribution, etc. |
2014 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
776p |
| 500 ## - GENERAL NOTE |
|---|
| General note |
Paperback / softback |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
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.<br/><br/>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.<br/><br/>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.<br/><br/>Accessible, including the basics of essential concepts of probability and random sampling<br/>Examples with R programming language and JAGS software<br/>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)<br/>Coverage of experiment planning<br/>R and JAGS computer programming code on website<br/>Exercises have explicit purposes and guidelines for accomplishment<br/>Provides step by step instructions on how to conduct Bayesian data analyses in the popular and free software R and WinBugs. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Applied mathematics |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name entry element |
Probability and statistics |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
