- Cover
- Title Page
- List of Figures
- List of Tables
- Preface
- Acknowledgments
- Part I: The Preliminaries
- Chapter 1: Why R?
- Chapter 2: The R Basics
- Chapter 3: Data Preparation and Other Tricks
- 3.1 Introduction
- 3.2 Manipulation with Complex Format Files
- 3.3 Reading Datasets of Foreign Formats
- 3.4 Displaying R Objects
- 3.5 Manipulation Using R Functions
- 3.6 Working with Time and Date
- 3.7 Text Manipulations
- 3.8 Scripts and Text Editors for R
- 3.9 Further Reading
- 3.10 Complements, Problems, and Programs
- Chapter 4: Exploratory Data Analysis
- Part II: Probability and Inference
- Chapter 5: Probability Theory
- 5.1 Introduction
- 5.2 Sample Space, Set Algebra, and Elementary Probability
- 5.3 Counting Methods
- 5.4 Probability: A Definition
- 5.5 Conditional Probability and Independence
- 5.6 Bayes Formula
- 5.7 Random Variables, Expectations, and Moments
- 5.8 Distribution Function, Characteristic Function, and Moment Generation Function
- 5.9 Inequalities
- 5.10 Convergence of Random Variables
- 5.11 The Law of Large Numbers
- 5.12 The Central Limit Theorem
- 5.13 Further Reading
- 5.14 Complements, Problems, and Programs
- Chapter 6: Probability and Sampling Distributions
- 6.1 Introduction
- 6.2 Discrete Univariate Distributions
- 6.3 Continuous Univariate Distributions
- 6.4 Multivariate Probability Distributions
- 6.5 Populations and Samples
- 6.6 Sampling from the Normal Distributions
- 6.7 Some Finer Aspects of Sampling Distributions
- 6.8 Multivariate Sampling Distributions
- 6.9 Bayesian Sampling Distributions
- 6.10 Further Reading
- 6.11 Complements, Problems, and Programs
- Chapter 7: Parametric Inference
- 7.1 Introduction
- 7.2 Families of Distribution
- 7.3 Loss Functions
- 7.4 Data Reduction
- 7.5 Likelihood and Information
- 7.6 Point Estimation
- 7.7 Comparison of Estimators
- 7.8 Confidence Intervals
- 7.9 Testing Statistical Hypotheses–The Preliminaries
- 7.10 The Neyman-Pearson Lemma
- 7.11 Uniformly Most Powerful Tests
- 7.12 Uniformly Most Powerful Unbiased Tests
- 7.13 Likelihood Ratio Tests
- 7.14 Behrens-Fisher Problem
- 7.15 Multiple Comparison Tests
- 7.16 The EM Algorithm*
- 7.17 Further Reading
- 7.18 Complements, Problems, and Programs
- Chapter 8: Nonparametric Inference
- Chapter 9: Bayesian Inference
- Chapter 5: Probability Theory
- Part III: Stochastic Processes and Monte Carlo
- Part IV: Linear Models
- Chapter 12: Linear Regression Models
- 12.1 Introduction
- 12.2 Simple Linear Regression Model
- 12.3 The Anscombe Warnings and Regression Abuse
- 12.4 Multiple Linear Regression Model
- 12.5 Model Diagnostics for the Multiple Regression Model
- 12.6 Multicollinearity
- 12.7 Data Transformations
- 12.8 Model Selection
- 12.9 Further Reading
- 12.10 Complements, Problems, and Programs
- Chapter 13: Experimental Designs
- Chapter 14: Multivariate Statistical Analysis - I
- 14.1 Introduction
- 14.2 Graphical Plots for Multivariate Data
- 14.3 Definitions, Notations, and Summary Statistics for Multivariate Data
- 14.4 Testing for Mean Vectors : One Sample
- 14.5 Testing for Mean Vectors : Two-Samples
- 14.6 Multivariate Analysis of Variance
- 14.7 Testing for Variance-Covariance Matrix: One Sample
- 14.8 Testing for Variance-Covariance Matrix: -Samples
- 14.9 Testing for Independence of Sub-vectors
- 14.10 Further Reading
- 14.11 Complements, Problems, and Programs
- Chapter 15: Multivariate Statistical Analysis - II
- Chapter 16: Categorical Data Analysis
- Chapter 17: Generalized Linear Models
- 17.1 Introduction
- 17.2 Regression Problems in Count/Discrete Data
- 17.3 Exponential Family and the GLM
- 17.4 The Logistic Regression Model
- 17.5 Inference for the Logistic Regression Model
- 17.6 Model Selection in Logistic Regression Models
- 17.7 Probit Regression
- 17.8 Poisson Regression Model
- 17.9 Further Reading
- 17.10 Complements, Problems, and Programs
- Chapter 12: Linear Regression Models
- Appendix A: Open Source Software–An Epilogue
- Appendix B: The Statistical Tables
- Bibliography
- End User License Agreement
A COURSE IN STATISTICS WITH R
Prabhanjan Narayanachar Tattar
Fractal Analytics Inc.
Suresh Ramaiah
Karnatak University, India
B.G. Manjunath
Dell International Services, India
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