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(Ebook) Beginning R: An Introduction to Statistical Programming by Larry Pace, Joshua Wiley ISBN 9781484203743, 1484203747

  • SKU: EBN-55460706
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Authors:Larry Pace, Joshua Wiley
Pages:350 pages.
Year:2015
Editon:2nd ed.
Publisher:Apress
Language:english
File Size:11.15 MB
Format:pdf
ISBNS:9781484203743, 1484203747
Categories: Ebooks

Product desciption

(Ebook) Beginning R: An Introduction to Statistical Programming by Larry Pace, Joshua Wiley ISBN 9781484203743, 1484203747

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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