Introduction to Bayesian Statistics

Name: Introduction to Bayesian Statistics
Price: 7.43 USD
Availability: InStock
ISBN: 9780470141151

ISBN-10: 0470141158

ISBN-13: 9780470141151

Edition: 2nd 2007 (Revised)

Authors: William M. Bolstad

List price: $160.00

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Description:

Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. This book uniquely covers the topics usually found in a typical introductory statistics book, but from a Bayesian perspective.

Book details

List price: $160.00
Edition: 2nd
Copyright year: 2007
Publisher: John Wiley & Sons, Incorporated
Publication date: 8/15/2007
Binding: Hardcover
Pages: 464
Size: 6.00" wide x 9.25" long x 1.00" tall
Weight: 1.694
Language: English

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.



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