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Index
Table of Contents
Part I: R Introduction
Chapter 1: Basic Data Types
Chapter 2: Vector
Chapter 3: Matrix
Chapter 4: List
Chapter 5: Data Frame
Part II: Elementary Statistics with R
Chapter 6: Qualitative Data
Chapter 7: Quantitative Data
Chapter 8: Numerical Measures
Chapter 9: Probability Distributions
Chapter 10: Interval Estimation
Chapter 11: Hypothesis Testing
Chapter 12: Type II Errors
Chapter 13: Inference About Two Populations
Chapter 14: Goodness of Fit
Chapter 15: Analysis of Variance
Chapter 16: Non-parametric Methods
Chapter 17: Simple Linear Regression
Chapter 18: Multiple Linear Regression
Chapter 19: Logistic Regression
Part III: Bayesian Statistics Using OpenBUGS
Chapter 20: Bayesian Discrete Inference
Chapter 21: Bayesian Binomial Inference
Chapter 22: Bayesian Poisson Inference
Chapter 23: Bayesian Inference for Normal Mean
Chapter 24: Bayesian Inference for Two Populations
Chapter 25: Bayesian Analysis of Variance
Chapter 26: Bayesian Simple Linear Regression
Chapter 27: Bayesian Multiple Linear Regression
Chapter 28: Bayesian Logistic Regression
Chapter 29: Hierarchical Models
Part IV: GPU Computing with R
Chapter 30: Statistical Computing on GPU
Appendix A: Installing GPU Packages
Appendix B: Installing R2OpenBUGS on Linux
References
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