- Home
- Computers
- Data Modeling & Design
- R in a Nutshell (A Desktop Quick Reference)
R in a Nutshell (A Desktop Quick Reference)
- Availability: Confirm prior to ordering
- Branding: minimum 50 pieces (add’l costs below)
- Check Freight Rates (branded products only)
Branding Options (v), Availability & Lead Times
- 1-Color Imprint: $2.00 ea.
- Promo-Page Insert: $2.50 ea. (full-color printed, single-sided page)
- Belly-Band Wrap: $2.50 ea. (full-color printed)
- Set-Up Charge: $45 per decoration
- Availability: Product availability changes daily, so please confirm your quantity is available prior to placing an order.
- Branded Products: allow 10 business days from proof approval for production. Branding options may be limited or unavailable based on product design or cover artwork.
- Unbranded Products: allow 3-5 business days for shipping. All Unbranded items receive FREE ground shipping in the US. Inquire for international shipping.
- RETURNS/CANCELLATIONS: All orders, branded or unbranded, are NON-CANCELLABLE and NON-RETURNABLE once a purchase order has been received.
Product Details
Overview
If you’re considering R for statistical computing and data visualization, this book provides a quick and practical guide to just about everything you can do with the open source R language and software environment. You’ll learn how to write R functions and use R packages to help you prepare, visualize, and analyze data. Author Joseph Adler illustrates each process with a wealth of examples from medicine, business, and sports.
Updated for R 2.14 and 2.15, this second edition includes new and expanded chapters on R performance, the ggplot2 data visualization package, and parallel R computing with Hadoop.
- Get started quickly with an R tutorial and hundreds of examples
- Explore R syntax, objects, and other language details
- Find thousands of user-contributed R packages online, including Bioconductor
- Learn how to use R to prepare data for analysis
- Visualize your data with R’s graphics, lattice, and ggplot2 packages
- Use R to calculate statistical fests, fit models, and compute probability distributions
- Speed up intensive computations by writing parallel R programs for Hadoop
- Get a complete desktop reference to R








