Introduction to Bayesian Statistics

by
Edition: 2nd
Format: Hardcover
Pub. Date: 2007-08-15
Publisher(s): Wiley-Interscience
List Price: $172.87

Buy New

Usually Ships in 3-4 Business Days
$164.64

Rent Textbook

Select for Price
There was a problem. Please try again later.

Used Textbook

We're Sorry
Sold Out

eTextbook

We're Sorry
Not Available

How Marketplace Works:

  • This item is offered by an independent seller and not shipped from our warehouse
  • Item details like edition and cover design may differ from our description; see seller's comments before ordering.
  • Sellers much confirm and ship within two business days; otherwise, the order will be cancelled and refunded.
  • Marketplace purchases cannot be returned to eCampus.com. Contact the seller directly for inquiries; if no response within two days, contact customer service.
  • Additional shipping costs apply to Marketplace purchases. Review shipping costs at checkout.

Summary

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(r) 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.

Author Biography

William M. Bolstad, PhD, is Senior Lecturer in the Department of Statistics at The University of Waikato, New Zealand. He holds degrees from the University of Missouri, Stanford University, and The University of Waikato. Dr. Bolstad's research interests include Bayesian statistics, MCMC methods, recursive estimation techniques, multiprocess dynamic time series models, and forecasting.

Table of Contents

Preface
Preface to First Edition
Introduction to Statistical Science
The Scientific Method: A Process for Learning
The Role of Statistics in the Scientific Method
Main Approaches to Statistics
Purpose and Organization of This Text
Scientific Data Gathering
Sampling from a Real Population
Observational Studies and Designed Experiments
Monte Carlo Exercises
Displaying and Summarizing Data
Graphically Displaying a Single Variable
Graphically Comparing Two Samples
Measures of Location
Measures of Spread
Displaying Relationships Between Two or More Variables
Measures of Association for Two or More Variables
Exercises
Logic, Probability, and Uncertainty
Deductive Logic and Plausible Reasoning
Probability
Axioms of Probability
Joint Probability and Independent Events
Conditional Probability
Bayes' Theorem
Assigning Probabilities
Odds Ratios and Bayes Factor
Beat the Dealer
Exercises
Discrete Random Variables
Discrete Random Variables
Probability Distribution of a Discrete Random Variable
Binomial Distribution
Hypergeometric Distribution
Poisson Distribution
Joint Random Variables
Conditional Probability for Joint Random Variables
Exercises
Bayesian Inference for Discrete Random Variables
Two Equivalent Ways of Using Bayes' Theorem
Bayes' Theorem for Binomial with Discrete Prior
Important Consequences of Bayes' Theorem
Bayes' theorem for Poisson with Discrete Prior
Exercises
Computer Exercises
Continuous Random Variables
Probability Density Function
Some Continuous Distributions
Joint Continuous Random Variables
Joint Continuous and Discrete Random Variables
Exercises
Bayesian Inference for Binomial Proportion
Using a Uniform Prior
Using a Beta Prior
Choosing Your Prior
Summarizing the Posterior Distribution
Estimating the Proportion
Bayesian Credible Interval
Exercises
Computer Exercises
Comparing Bayesian and Frequentist Inferences for Proportion
Frequentist Interpretation of Probability and Parameters
Point Estimation
Comparing Estimators for Proportion
Interval Estimation
Hypothesis Testing
Testing a OneSided Hypothesis
Testing a TwoSided Hypothesis
Exercises
Carlo Exercises
Bayesian Inference for Poisson
Some Prior Distributions for Poisson
Inference for Poisson Parameter
Exercises
Computer Exercises
Bayesian Inference for Normal Mean
Bayes' Theorem for Normal Mean with a Discrete Prior
Bayes' Theorem for Normal Mean with a Continuous Prior
Choosing Your Normal Prior
Bayesian Credible Interval for Normal Mean
Predictive Density for Next Observation
Exercises
Computer Exercises
Comparing Bayesian and Frequentist Inferences for Mean
Comparing Frequentist and Bayesian Point Estimators
Comparing Confidence and Credible Intervals for Mean
Testing a OneSided Hypothesis about a Normal Mean
Testing a TwoSided Hypothesis about a Normal Mean
Exercises
Bayesian Infer
Table of Contents provided by Publisher. All Rights Reserved.

An electronic version of this book is available through VitalSource.

This book is viewable on PC, Mac, iPhone, iPad, iPod Touch, and most smartphones.

By purchasing, you will be able to view this book online, as well as download it, for the chosen number of days.

Digital License

You are licensing a digital product for a set duration. Durations are set forth in the product description, with "Lifetime" typically meaning five (5) years of online access and permanent download to a supported device. All licenses are non-transferable.

More details can be found here.

A downloadable version of this book is available through the eCampus Reader or compatible Adobe readers.

Applications are available on iOS, Android, PC, Mac, and Windows Mobile platforms.

Please view the compatibility matrix prior to purchase.