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."โStatistics in Medical Research"[This book] is written in a lucid conversational style, which is so rare in mathemat
Introduction to Bayesian Statistics, Second Edition
โ Scribed by William M. Bolstad(auth.)
- Year
- 2007
- Tongue
- English
- Leaves
- 448
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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."
โStatistics 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."
โSTATS: 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."
โJournal 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 bookโbut from a Bayesian perspectiveโgiving 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 Minitabยฎ 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.Content:
Chapter 1 Introduction to Statistical Science (pages 1โ11):
Chapter 2 Scientific Data Gathering (pages 13โ28):
Chapter 3 Displaying and Summarizing Data (pages 29โ54):
Chapter 4 Logic, Probability, and Uncertainty (pages 55โ76):
Chapter 5 Discrete Random Variables (pages 77โ100):
Chapter 6 Bayesian Inference for Discrete Random Variables (pages 101โ119):
Chapter 7 Continuous Random Variables (pages 121โ140):
Chapter 8 Bayesian Inference for Binomial Proportion (pages 141โ159):
Chapter 9 Comparing Bayesian and Frequentist Inferences for Proportion (pages 161โ181):
Chapter 10 Bayesian Inference for Poisson (pages 183โ198):
Chapter 11 Bayesian Inference for Normal Mean (pages 199โ222):
Chapter 12 Comparing Bayesian and Frequentist Inference for Mean (pages 223โ238):
Chapter 13 Bayesian Inference for Difference Between Means (pages 239โ265):
Chapter 14 Bayesian Inference for Simple Linear Regression (pages 267โ295):
Chapter 15 Bayesian Inference for Standard Deviation (pages 297โ316):
Chapter 16 Robust Bayesian Methods (pages 317โ332):
๐ SIMILAR VOLUMES
This book presents Bayesโ theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters. It does so in a simple manner that is easy to comprehend. The book compares traditional and Bayesian methods with the
Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and th
<p><P>From the reviews of the second edition:</P><P></P><P>"This is a well-written introduction to Bayesian Analysis that contains many applications to Geodesy and Engineering at the cutting edge of these topics. โฆ There is a good treatment of Bayesian Analysis of Linear Models โฆ . The references ar