1. 25 Recipes for Getting Started with R
Description:
R is a powerful tool for statistics and graphics, but getting started with this language can be frustrating. This short, concise book provides beginners with a selection of how-to recipes to solve simple problems with R. Each solution gives you just what you need to know to use R for basic statistics, graphics, and regression.
You'll find recipes on reading data files, creating data frames, computing basic statistics, testing means and correlations, creating a scatter plot, performing simple linear regression, and many more. These solutions were selected from O'Reilly'sR Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics.
With more than 200 practical recipes, this book helps you perform data analysis with R quickly and efficiently. The R language provides everything you need to do statistical work, but its structure can be difficult to master. This collection of concise, task-oriented recipes makes you productive with R immediately, with solutions ranging from basic tasks to input and output, general statistics, graphics, and linear regression.
Each recipe addresses a specific problem, with a discussion that explains the solution and offers insight into how it works. If you’re a beginner, R Cookbook will help get you started. If you’re an experienced data programmer, it will jog your memory and expand your horizons. You’ll get the job done faster and learn more about R in the process.
Create vectors, handle variables, and perform other basic functions
Input and output data
Tackle data structures such as matrices, lists, factors, and data frames
Work with probability, probability distributions, and random variables
Calculate statistics and confidence intervals, and perform statistical tests
Create a variety of graphic displays
Build statistical models with linear regressions and analysis of variance (ANOVA)
Explore advanced statistical techniques, such as finding clusters in your data
"Wonderfully readable, R Cookbook serves not only as a solutions manual of sorts, but as a truly enjoyable way to explore the R language—one practical example at a time."—Jeffrey Ryan, software consultant and R package author
3. Exploring Everyday Things with R and Ruby
Discover the world around you through programming Description:
If you’re curious about how things work, this fun and intriguing guide will help you find real answers to everyday problems. By using fundamental math and doing simple programming with the Ruby and R languages, you’ll learn how to model a problem and work toward a solution.
All you need is a basic understanding of programming. After a quick introduction to Ruby and R, you’ll explore a wide range of questions by learning how to assemble, process, simulate, and analyze the available data. You’ll learn to see everyday things in a different perspective through simple programs and common sense logic. Once you finish this book, you can begin your own journey of exploration and discovery.
Here are some of the questions you’ll explore:
Determine how many restroom stalls can accommodate an office with 70 employees
Mine your email to understand your particular emailing habits
Use simple audio and video recording devices to calculate your heart rate
Create an artificial society—and analyze its behavioral patterns to learn how specific factors affect our real society
4. Data Mashups in R
A Case Study in Real-World Data Analysis
Description:
How do you use R to import, manage, visualize, and analyze real-world data? With this short, hands-on tutorial, you learn how to collect online data, massage it into a reasonable form, and work with it using R facilities to interact with web servers, parse HTML and XML, and more. Rather than use canned sample data, you'll plot and analyze current home foreclosure auctions in Philadelphia.
This practical mashup exercise shows you how to access spatial data in several formats locally and over the Web to produce a map of home foreclosures. It's an excellent way to explore how the R environment works with R packages and performs statistical analysis.
Parse messy data from public foreclosure auction postings
Plot the data using R's PBSmapping package
Import US Census data to add context to foreclosure data
Use R's lattice and latticeExtra packages for data visualization
Create multidimensional correlation graphs with the pairs() scatterplot matrix package
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