Introduction to Bayesian statistics /
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| Author / Creator: | Bolstad, William M., 1943- |
|---|---|
| Edition: | 2nd ed. |
| Imprint: | Hoboken, N.J. : John Wiley, c2007. |
| Description: | xxiv, 437 p. : ill. ; 25 cm. |
| Language: | English |
| Subject: | |
| Format: | E-Resource Print Book |
| URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/6490189 |
Table of Contents:
- Preface
- Preface to First Edition
- 1. Introduction to Statistical Science
- 1.1. The Scientific Method: A Process for Learning
- 1.2. The Role of Statistics in the Scientific Method
- 1.3. Main Approaches to Statistics
- 1.4. Purpose and Organization of This Text
- 2. Scientific Data Gathering
- 2.1. Sampling from a Real Population
- 2.2. Observational Studies and Designed Experiments
- Monte Carlo Exercises
- 3. Displaying and Summarizing Data
- 3.1. Graphically Displaying a Single Variable
- 3.2. Graphically Comparing Two Samples
- 3.3. Measures of Location
- 3.4. Measures of Spread
- 3.5. Displaying Relationships Between Two or More Variables
- 3.6. Measures of Association for Two or More Variables
- Exercises
- 4. Logic, Probability, and Uncertainty
- 4.1. Deductive Logic and Plausible Reasoning
- 4.2. Probability
- 4.3. Axioms of Probability
- 4.4. Joint Probability and Independent Events
- 4.5. Conditional Probability
- 4.6. Bayes' Theorem
- 4.7. Assigning Probabilities
- 4.8. Odds Ratios and Bayes Factor
- 4.9. Beat the Dealer
- Exercises
- 5. Discrete Random Variables
- 5.1. Discrete Random Variables
- 5.2. Probability Distribution of a Discrete Random Variable
- 5.3. Binomial Distribution
- 5.4. Hypergeometric Distribution
- 5.5. Poisson Distribution
- 5.6. Joint Random Variables
- 5.7. Conditional Probability for Joint Random Variables
- Exercises
- 6. Bayesian Inference for Discrete Random Variables
- 6.1. Two Equivalent Ways of Using Bayes' Theorem
- 6.2. Bayes' Theorem for Binomial with Discrete Prior
- 6.3. Important Consequences of Bayes' Theorem
- 6.4. Bayes' theorem for Poisson with Discrete Prior
- Exercises
- Computer Exercises
- 7. Continuous Random Variables
- 7.1. Probability Density Function
- 7.2. Some Continuous Distributions
- 7.3. Joint Continuous Random Variables
- 7.4. Joint Continuous and Discrete Random Variables
- Exercises
- 8. Bayesian Inference for Binomial Proportion
- 8.1. Using a Uniform Prior
- 8.2. Using a Beta Prior
- 8.3. Choosing Your Prior
- 8.4. Summarizing the Posterior Distribution
- 8.5. Estimating the Proportion
- 8.6. Bayesian Credible Interval
- Exercises
- Computer Exercises
- 9. Comparing Bayesian and Frequentist Inferences for Proportion
- 9.1. Frequentist Interpretation of Probability and Parameters
- 9.2. Point Estimation
- 9.3. Comparing Estimators for Proportion
- 9.4. Interval Estimation
- 9.5. Hypothesis Testing
- 9.6. Testing a OneSided Hypothesis
- 9.7. Testing a TwoSided Hypothesis
- Exercises
- Carlo Exercises
- 10. Bayesian Inference for Poisson
- 10.1. Some Prior Distributions for Poisson
- 10.2. Inference for Poisson Parameter
- Exercises
- Computer Exercises
- 11. Bayesian Inference for Normal Mean
- 11.1. Bayes' Theorem for Normal Mean with a Discrete Prior
- 11.2. Bayes' Theorem for Normal Mean with a Continuous Prior
- 11.3. Choosing Your Normal Prior
- 11.4. Bayesian Credible Interval for Normal Mean
- 11.5. Predictive Density for Next Observation
- Exercises
- Computer Exercises
- 12. Comparing Bayesian and Frequentist Inferences for Mean
- 12.1. Comparing Frequentist and Bayesian Point Estimators
- 12.2. Comparing Confidence and Credible Intervals for Mean
- 12.3. Testing a OneSided Hypothesis about a Normal Mean
- 12.4. Testing a TwoSided Hypothesis about a Normal Mean
- Exercises
- 13. Bayesian Infer
