MARC details
| 000 -LEADER |
|---|
| fixed length control field |
03034nam a22003137a 4500 |
| 001 - CONTROL NUMBER |
|---|
| control field |
19630517 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
IIITD |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20240121020002.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
230715b xxu||||| |||| 00| 0 eng d |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
|---|
| LC control number |
2017942214 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9781473916364 |
| 035 ## - SYSTEM CONTROL NUMBER |
|---|
| System control number |
(OCoLC)on1020621409 |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
UKUOY |
| Language of cataloging |
eng |
| Transcribing agency |
UKUOY |
| Description conventions |
rda |
| Modifying agency |
YDX |
| -- |
BDX |
| -- |
UKUOY |
| -- |
OCLCO |
| -- |
WURST |
| -- |
OCLCF |
| -- |
OUP |
| -- |
IIITD |
| 042 ## - AUTHENTICATION CODE |
|---|
| Authentication code |
lccopycat |
| 050 00 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA279.5 |
| Item number |
.L36 2018 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.542 |
| Edition number |
23 |
| Item number |
LAM-S |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Lambert, Ben |
| 245 12 - TITLE STATEMENT |
|---|
| Title |
A student's guide to Bayesian Statistics |
| Statement of responsibility, etc |
by Ben Lambert |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Place of publication, distribution, etc |
London : |
| Name of publisher, distributor, etc |
SAGE, |
| Date of publication, distribution, etc |
©2018 |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xx, 498 p. : |
| Other physical details |
ill. ; |
| Dimensions |
25 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
This book includes bibliographical references and an index. |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
An introduction to Bayesian inference -- Understanding the Bayesian formula -- Analytic Bayesian methods -- A practical guide to doing real-life Bayesian analysis: Computational Bayes -- Hierarchical models and regression. |
| Title |
1: How to best use this book |
| -- |
2: The subjective worlds of Frequentist and Bayesian statistics |
| -- |
3: Probability - the nuts and bolts of Bayesian inference |
| -- |
4: Likelihoods |
| -- |
5: Priors |
| -- |
6: The devil’s in the denominator |
| -- |
7: The posterior - the goal of Bayesian inference |
| -- |
8: An introduction to distributions for the mathematically-un-inclined |
| -- |
9: Conjugate priors |
| -- |
10: Evaluation of model fit and hypothesis testing |
| -- |
11: Making Bayesian analysis objective? |
| -- |
12: Leaving conjugates behind: Markov Chain Monte Carlo |
| -- |
13: Random Walk Metropolis |
| -- |
14: Gibbs sampling |
| -- |
15: Hamiltonian Monte Carlo |
| -- |
16: Stan |
| -- |
17: Hierarchical models |
| -- |
18: Linear regression models |
| -- |
19: Generalised linear models and other animals |
| -- |
Bibliography |
| -- |
Index |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
"Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics. Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at statistics and Bayesian newcomers. Through a logical structure that introduces and builds upon key concepts in a gradual way and slowly acclimatizes students to using R and Stan software, the book covers: An introduction to probability and Bayesian inference, Understanding Bayes' rule, Nuts and bolts of Bayesian analytic methods, Computational Bayes and real-world Bayesian analysis, Regression analysis and hierarchical methods. This unique guide will help students develop the statistical confidence and skills to put the Bayesian formula into practice, from the basic concepts of statistical inference to complex applications of analyses." -- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Bayesian statistical decision theory. |
| 650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Bayesian statistical decision theory. |
| Source of heading or term |
fast |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
|---|
| a |
7 |
| b |
cbc |
| c |
copycat |
| d |
2 |
| e |
ncip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Books |
| Koha issues (borrowed), all copies |
2 |
