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Über dieses Buch

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 AT&T. 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

Inhaltsverzeichnis

Frontmatter

2012 | OriginalPaper | Buchkapitel

Chapter 1. Getting R and Getting Started

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 2. Programming in R

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 3. Writing Reusable Functions

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 4. Summary Statistics

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 5. Creating Tables and Graphs

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 6. Discrete Probability Distributions

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 7. Computing Normal Probabilities

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 8. Creating Confidence Intervals

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 9. Performing t Tests

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 10. One-Way Analysis of Variance

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 11. Advanced Analysis of Variance

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 12. Correlation and Regression

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 13. Multiple Regression

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 14. Logistic Regression

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 15. Chi-Square Tests

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 16. Nonparametric Tests

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 17. Using R for Simulation

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 18. The “New” Statistics: Resampling and Bootstrapping

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 19. Making an R Package

Larry Pace

2012 | OriginalPaper | Buchkapitel

Chapter 20. The R Commander Package

Larry Pace

Backmatter

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