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Beginning R = an introduction to sta...

Wiley, Joshua F.

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Beginning R = an introduction to statistical programming /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Beginning R/ by Joshua F. Wiley, Larry A. Pace.
Reminder of title:	an introduction to statistical programming /
Author:	Wiley, Joshua F.
other author:	Pace, Larry A.
Published:	Berkeley, CA :Apress : : 2015.,
Description:	xxiii, 327 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	R (Computer program language) -
Online resource:	http://dx.doi.org/10.1007/978-1-4842-0373-6
ISBN:	9781484203736

Beginning R = an introduction to statistical programming /
Wiley, Joshua F.

Beginning Ran introduction to statistical programming /[electronic resource] :by Joshua F. Wiley, Larry A. Pace. - 2nd ed. - Berkeley, CA :Apress :2015. - xxiii, 327 p. :ill., digital ;24 cm.

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.

ISBN: 9781484203736

Standard No.: 10.1007/978-1-4842-0373-6doiSubjects--Topical Terms:

784593
R (Computer program language)

LC Class. No.: QA276.45.R3

Dewey Class. No.: 005.133

Beginning R = an introduction to statistical programming /
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520 $a 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.
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