Beginning R
An Introduction to Statistical Programming
Nonfiction, Computers, Programming, Programming Languages, Application Software, General Computing
| Author: | Larry Pace, Joshua Wiley | ISBN: | 9781484203736 |
| Publisher: | Apress | Publication: | October 23, 2015 |
| Imprint: | Apress | Language: | English |
| Author: | Larry Pace, Joshua Wiley |
| ISBN: | 9781484203736 |
| Publisher: | Apress |
| Publication: | October 23, 2015 |
| Imprint: | Apress |
| Language: | English |
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3.
R is a powerful open-source language and programming environment for statistics 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, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. 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 data analysis and research.
What You Will Learn:
-
How to acquire and install R
-
Hot to import and export data and scripts
-
How to analyze data and generate graphics
-
How to program in R to write custom functions
-
Hot to use R for interactive statistical explorations
-
How to conduct bootstrapping and other advanced techniques
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based approach incorporating best practices with clear explanations of the statistics being done. It has been completely re-written since the first edition to make use of the latest packages and features in R version 3.
R is a powerful open-source language and programming environment for statistics 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, with a constantly evolving ecosystem of packages providing new functionality for data analysis. R has also become popular in commercial use at companies such as Microsoft, Google, and Oracle. 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 data analysis and research.
What You Will Learn:
-
How to acquire and install R
-
Hot to import and export data and scripts
-
How to analyze data and generate graphics
-
How to program in R to write custom functions
-
Hot to use R for interactive statistical explorations
-
How to conduct bootstrapping and other advanced techniques
