Probability and statistics with R / created by Maria Dolres Ugarte, Ana F Militino and Alan T Arnholt.

Includes bibliographical references and index

1. A Brief Introduction to S
2. Exploring Data
3. General Probability and Random Variables
4. Univariate Probability Distributions
5. Multivariate Probability Distributions
6. Sampling and Sampling Distributions
7. Point Estimation
8. Confidence Intervals
9. Hypothesis Testing
10. Nonparametric Methods
11. Experimental Design
12. Regression
A.S Commands
B. Quadratic Forms and Random Vectors and Matrices

Probability and Statistics with R shows how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs to facilitate hands-on comprehension." "Integrating theory with practice, the text briefly introduces the syntax, structures, and functions of the S language, before covering important graphically and numerically descriptive methods. The next several chapters elucidate probability and random variables topics, including univariate and multivariate distributions. After exploring sampling distributions, the authors discuss point estimation, confidence intervals, hypothesis testing, and a wide range of nonparametric methods. With a focus on experimental design, the book also presents fixed- and random-effects models as well as randomized block and two-factor factorial designs. The final chapter describes simple and multiple regression analyses." "This comprehensive book presents extensive treatments of data analysis using parametric and nonparametric techniques. It effectively links statistical concepts with R procedures, enabling the application of the language to the vast world of statistics."