# Introduction to Bayesian statistics / William M. Bolstad.

##### By: Bolstad, William M

Material type: TextLanguage: English Publisher: Hoboken, N.J. : John Wiley, c2007Edition: 2nd edDescription: xxiv, 437 p. : ill. ; 25 cmISBN: 9780470141151; 0470141158Subject(s): Bayesian statistical decision theoryDDC classification: 519.542 LOC classification: QA279.5 | .B65 2007Online resources: Table of contents only | Contributor biographical information | Publisher description | WorldCat Details | E-book FulltextItem type | Current location | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds |
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E-Book | EWU Library E-book | Non-fiction | 519.542 BOI 2007 (Browse shelf) | Not For Loan | ||||

Text | EWU Library Reserve Section | Non-fiction | 519.542 BOI 2007 (Browse shelf) | C-1 | Not For Loan | 25697 |

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519.54 RAM 2012 Multilevel and longitudinal modeling using Stata / | 519.54 SIS 2003 Statistical inference / | 519.54 SPA 2007 Applied nonparametric statistical methods / | 519.542 BOI 2007 Introduction to Bayesian statistics / | 519.542 COA 2014 Applied Bayesian modelling / | 519.542 LEB 2012 Bayesian statistics : | 519.542 LIS 2008 Statistical decision theory : |

Online version:

Bolstad, William M., 1943-

Introduction to Bayesian statistics.

Hoboken, N.J. : John Wiley, c2007

(OCoLC)654593316

Includes bibliographical references (p. 431-432) and index.

Table of contents Introduction to statistical science --

Scientific data gathering --

Displaying and summarizing data --

Logic, probability, and uncertainty --

Discrete random variables --

Bayesian inference for discrete random variables --

Continuous random variables --

Bayesian inference for binomial proportion --

Comparing Bayesian and frequentist inferences for proportion --

Bayesian inference for poisson --

Bayesian inference for normal mean --

Comparing Bayesian and frequentist inferences for mean --

Bayesian inference for difference between means --

Bayesian inference for single linear regression --

Bayesian inference for standard deviation --

Robust Bayesian methods.

Summary:

Covers the topics typically found in an introductory statistics book-but from a Bayesian perspective-giving readers an advantage as they enter fields where statistics is used.

Applied Statistics

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