Book description
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
What you'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 contents
- Title
- Dedication
- Contents at a Glance
- Contents
- About the Author
- About the Technical Reviewer
- Acknowledgments
- Introduction
- Chapter 1: Getting R and Getting Started
-
Chapter 2: Programming in R
- What is Programming?
- Getting Ready to Program
- The Requirements for Learning to Program
- Flow Control
- Essentials of R Programming
- Understanding the R Environment
- Implementation of Program Flow in R
- A First R Program
- Another Example—Finding Pythagorean Triples
- Using R to Solve Quadratic Equations
- Why R is Object-Oriented
- Conclusion
-
Chapter 3: Writing Reusable Functions
- Examining an R Function from the Base R Code
- Creating a Function
- Calculating a Confidence Interval for a Mean
- Avoiding Loops with Vectorized Operations
- Vectorizing If-Else Statements Using ifelse()
- Making More Powerful Functions
- Any, All, and Which
- Making Functions More Useful
- Confidence Intervals Revisited
- Conclusion
- Chapter 4: Summary Statistics
- Chapter 5: Creating Tables and Graphs
- Chapter 6: Discrete Probability Distributions
- Chapter 7: Computing Normal Probabilities
- Chapter 8: Creating Confidence Intervals
- Chapter 9: Performing t Tests
- Chapter 10: One-Way Analysis of Variance
- Chapter 11: Advanced Analysis of Variance
- Chapter 12: Correlation and Regression
- Chapter 13: Multiple Regression
- Chapter 14: Logistic Regression
- Chapter 15: Chi-Square Tests
- Chapter 16: Nonparametric Tests
- Chapter 17: Using R for Simulation
- Chapter 18: The “New” Statistics: Resampling and Bootstrapping
- Chapter 19: Making an R Package
- Chapter 20: The R Commander Package
- Index
Product information
- Title: Beginning R: An Introduction to Statistical Programming
- Author(s):
- Release date: October 2012
- Publisher(s): Apress
- ISBN: 9781430245544
You might also like
book
Beginning R: An Introduction to Statistical Programming, Second Edition
Beginning R, Second Edition is a hands-on book showing how to use the R language, write …
book
Using R and RStudio for Data Management, Statistical Analysis, and Graphics, 2nd Edition
This book covers the aspects of R most often used by statistical analysts. Incorporating the use …
book
Understanding and Applying Basic Statistical Methods Using R
Features a straightforward and concise resource for introductory statistical concepts, methods, and techniques using R Understanding …
book
Mathematical Statistics
Explores mathematical statistics in its entirety—from the fundamentals to modern methods This book introduces readers to …