PROBABILITY AND STATISTICS WITH R

　　本書整合統計方法理論，以實例說明及課後練習，搭配R語言的實作，有助於學生對基礎機率統計的了解與學習。

　　Designed for an intermediate undergraduate course, Probability and Statistics with R shows students 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 learning.

　　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.

　　Demonstrating that R can be used as a powerful teaching aid, this comprehensive text 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.

Ch1: A Brief Introduction to S
Ch2: Exploring Data
Ch3: General Probability and Random Variables
Ch4: Univariate Probability Distributions
Ch5: Multivariate Probability Distributions
Ch6: Sampling and Sampling Distributions
Ch7: Point Estimation
Ch8: Confidence Intervals
Ch9: Hypothesis Testing
Ch10: Nonparametric Methods
Ch11: Experimental Design
Ch12: Regression
Appendix A: S Commands
Appendix B: Quadratic Forms and Random Vectors and Matrices
References
Index