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R is a powerful open source programming language for statistical analysis. R is known for its active user community, its robust packages, flexibility and graphics.

**Where can I find R?**

You can get R for your computer along with full documentation from www.r-project.org

R is available in the DataLab (tisch library) and on the collaborative workstation computers and Room 224 in Tisch Library.

- Analyze Survey DataGreat resource providing survey data analysis methodologies in R
- Quick-Ra guide for experienced users of other stats packages like SAS, SPSS, or Stata.
- R API/FeedsA list of available APIs that can be read as packages into R
- R SeekHave you tried searching "R" in a search engine? Try this instead.
- R Starter KitCreated by UCLA
- R Tutorial VideosVideo tutorial set from the University of Colorado Denver. Contains sample datasets to follow along with. The video above is first video in this series.
- R Twotorialsfrom the website: "how to do stuff in r. two minutes or less."
- Stats TeachRCreated by a UMass Amherst Biostatistics student. statsTeachR is an open-access, online repository of modular lesson plans, a.k.a. "modules", for teaching statistics using R at the undergraduate and graduate level. Each module focuses on teaching a specific statistical concept. The modules range from introductory lessons in statistics and statistical computing to more advanced topics in statistics and biostatistics.

- 25 Recipes for Getting Started with R by Paul TeetorISBN: 9781449303235Publication Date: 2011-03-07R 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's R Cookbook, which contains more than 200 recipes for R that you'll find useful once you move beyond the basics.
- A Beginner's Guide to R by Alain F. Zuur; Elena N. Ieno; Erik H. W. G. MeestersCall Number: QA276.45.R3 Z88 2009ISBN: 9780387938370Publication Date: 2009-01-01Based on their extensive experience with teaching R and statistics to applied scientists, the authors provide a beginner's guide to R. The text covers how to download and install R, import and manage data, elementary plotting, an introduction to functions, advanced plotting, and common beginner mistakes.--[book cover]
- Beginning R by Mark GardenerISBN: 9781118164303Publication Date: 2012-06-05Conquer the complexities of this open source statistical language R is fast becoming the de facto standard for statistical computing and analysis in science, business, engineering, and related fields. This book examines this complex language using simple statistical examples, showing how R operates in a user-friendly context.
- Ggplot2 by Hadley WickhamISBN: 9780387981413Book on using the Ggplot2 package of R for data visualizations
- Qualitative Comparative Analysis with R by Alrik Thiem; Adrian DuaISBN: 9781461445838Publication Date: 2012-08-30Social science theory often builds on sets and their relations. Correlation-based methods of scientific enquiry, however, use linear algebra and are unsuited to analyzing set relations. The development of Qualitative Comparative Analysis (QCA) by Charles Ragin has given social scientists a formal tool for identifying set-theoretic connections based on Boolean algebra. As a result, interest in this method has markedly risen among social scientists in recent years. This book offers the first complete introduction on how to perform QCA in the R software environment for statistical computing and graphics with the QCA package.
- R Cookbook by Paul TeetorISBN: 9780596809157Publication Date: 2011-03-22With 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.
- R in a Nutshell by Joseph AdlerISBN: 144931208XPublication Date: 2012-10-16If youre 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.

- Last Updated: Nov 10, 2024 8:37 PM
- URL: https://researchguides.library.tufts.edu/SocSciData
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