Introduction to Bayesian Statistics PDF

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Download PRETITLE Introduction to Bayesian Statistics [Kindle Edition] POSTTITLE from mediafire, rapishare, and mirror link 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."
—Statistics 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."
—STATS: 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."
—Journal 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 book—but from a Bayesian perspective—giving 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 Minitab® 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.Direct download links available for PRETITLE Introduction to Bayesian Statistics [Kindle Edition] POSTTITLE

• Product Details
• Table of Contents
• Reviews

• File Size: 6751 KB
• Print Length: 464 pages
• Publisher: Wiley-Interscience; 2 edition (June 5, 2013)
• Sold by: Amazon Digital Services, Inc.
• Language: English
• ASIN: B00D8XUJA2
• Text-to-Speech: Enabled
• X-Ray:
  Not Enabled
• Lending: Enabled
• Amazon Best Sellers Rank: #220,370 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
  • #23 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Biological Sciences > Biostatistics
  • #50 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Medical eBooks > Research
• #23 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Professional Science > Biological Sciences > Biostatistics
• #50 in Kindle Store > Kindle eBooks > Nonfiction > Professional & Technical > Medical eBooks > Research

Introduction to Bayesian Statistics PDF

I have been searching for an introductory textbook that approaches statistics from the Bayesian perspective. This book does it, and it does it well! Based on what I have read, I will be trying to offer a class based on this book. The prerequisites are reasonable: good algebra skills and a general familiarity with calculus. The lack of colorful graphics means the students have to be pretty self-motivated. Personally, I wish I had found this when I was learning statistics.

By M. Schneider

Though quite expensive, this book is really a must-have for people with remote mathematical background needing to discover the bayesian approach. It is writtent as a complete course of introduction to statistics, but from the bayesian perspective. Personnaly, I never met the concepts so precisely explained, and would strongly advise anyone that wishes to be introduced with bayesian statistics to start here.

By L. Antoine