# Beginning R

4.11 - 1251 ratings - Source

Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by ATaT. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done What youall learn Acquire and install R Import and export data and scripts Generate basic statistics and graphics Program in R to write custom functions Use R for interactive statistical explorations Implement simulations and other advanced techniques Who this book is for Beginning R: An Introduction to Statistical Programming is an easy-to-read book that serves as an instruction manual and reference for working professionals, professors, and students who want to learn and use R for basic statistics. It is the perfect book for anyone needing a free, capable, and powerful tool for exploring statistics and automating their use. Table of ContentsPart I. Learning the R Language 1. Getting R and Getting Started 2. Programming in R 3. Writing Reusable Functions 4. Summary Statistics Part II. Using R for Descriptive Statistics 5. Creating Tables and Graphs 6. Discrete Probability Distributions 7. Computing Standard Normal Probabilities Part III. Using R for Inferential Statistics 8. Creating Confidence Intervals 9. Performing t Tests 10. Implementing One-Way ANOVA 11. Implementing Advanced ANOVA 12. Simple Correlation and Regression in R 13. Multiple Correlation and Regression in R 14. Logistic Regression 15. Performing Chi-Square Tests 16. Working in Nonparametric Statistics Part IV. Taking R to the Next Level 17. Using R for Simulation 18. Resampling and Bootstrapping 19. Creating R Packages 20. Executing R Packages... 0.9227206 0.9659254 0.9619243 0 9771208 1.0000000 Yr_2010 0.8645345 0.8885372 0.9070487 0.9533224 ... For example: agt; head(Mileages) Year Mfr Division Carline Displ Cyl Trans City Hwy Combined 1 2012 aston martin Aston Martin Lagonda Ltd V12 Vantage 5.9 12 Manual(M6) 11 ... Lagonda Ltd V8 Vantage S 4.7 8 Auto(AM7) 14 21 16 6 2012 Audi Audi R8 4.2 8 Auto(AM6) 13 21 16 Trans.

 Title : Beginning R Author : Larry Pace Publisher : Apress - 2012-10-17