9781449357108-1449357105-Learning R: A Step-by-Step Function Guide to Data Analysis

Learning R: A Step-by-Step Function Guide to Data Analysis

ISBN-13: 9781449357108
ISBN-10: 1449357105
Edition: 1
Author: Richard Cotton
Publication date: 2013
Publisher: O'Reilly Media
Format: Paperback 396 pages
FREE US shipping
Rent
35 days
from $33.16 USD
FREE shipping on RENTAL RETURNS
Buy

From $12.98

Rent

From $33.16

Book details

ISBN-13: 9781449357108
ISBN-10: 1449357105
Edition: 1
Author: Richard Cotton
Publication date: 2013
Publisher: O'Reilly Media
Format: Paperback 396 pages

Summary

Learning R: A Step-by-Step Function Guide to Data Analysis (ISBN-13: 9781449357108 and ISBN-10: 1449357105), written by authors Richard Cotton, was published by O'Reilly Media in 2013. With an overall rating of 4.5 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data, Data Mining, Data Processing, Microsoft Programming, Programming, Mathematical & Statistical, Software, Programming Languages, Bioinformatics, Biological Sciences) books. You can easily purchase or rent Learning R: A Step-by-Step Function Guide to Data Analysis (Paperback, Used) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $2.

Description

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you’ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.

The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you’ve learned, and concludes with exercises, most of which involve writing R code.

  • Write a simple R program, and discover what the language can do
  • Use data types such as vectors, arrays, lists, data frames, and strings
  • Execute code conditionally or repeatedly with branches and loops
  • Apply R add-on packages, and package your own work for others
  • Learn how to clean data you import from a variety of sources
  • Understand data through visualization and summary statistics
  • Use statistical models to pass quantitative judgments about data and make predictions
  • Learn what to do when things go wrong while writing data analysis code
Rate this book Rate this book

We would LOVE it if you could help us and other readers by reviewing the book