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Introduction to R

Introduction to R. Clay Ford, StatLab. September 11/12, 2013. Research Data Services. Research Data Services: http://www.library.virginia.edu/services / Data management planning GIS training and consultations Locating data, sharing and archiving data StatLab Services:

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Introduction to R

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  1. Introduction to R Clay Ford, StatLab September 11/12, 2013

  2. Research Data Services • Research Data Services: • http://www.library.virginia.edu/services/ • Data management planning • GIS training and consultations • Locating data, sharing and archiving data • StatLab Services: • http://statlab.library.virginia.edu/ • Individual consulting: advice, training, feedback on quantitative research • Workshops on statistical methods and techniques

  3. Introducing R • The facts: • R is a language and environment for statistical computing and graphics • Freely available and maintained by volunteers • R is extensible; can be expanded by installing “packages” • How to get it: • http://www.r-project.org/ (or Google “Download R”) • Available for Windows, Mac, Linux • Free to install, no catches • Also highly recommended: • R Studio: a free IDE for R • http://www.rstudio.com/ • If you install R and R Studio, then you only need to run R Studio

  4. Using R • R is command-line driven (very little point-and-click) • You use “functions” to work with data • Most analyses require writing a script, which is sourced into the R console • R Studio makes this process easier • What’s so special about R? • Free • Over 4000 packages that add functionality (about 25 come with R) • Produces nice print-ready graphics • Open-source (you can see how it does what it does) • Easy to install and non-invasive

  5. Assumptions, Goals, Expectations • Assumptions • No experience with R • Familiarity with basic statistical concepts • Goals • Get you comfortable enough to start using R • Give you with example code you can use and resources to learn more • Expectations • You will not learn R in a 90 minute workshop • You must use R to learn R

  6. Workshop Plan • If you have R and R Studio installed, please do the following: • Download R script (the file with .R extension): • Go to http://statlab.library.virginia.edu/ • Go to Workshop Descriptions under Workshop Schedule • Go to Introduction to R section and click “Download materials for the workshop” • Download the file with a .R extension (may need to right click and “Save Link As…”) • Open R Studio only (do not need to open R) • Open R script in R Studio. File…Open File… • Follow along with presentation • Let’s go use R!

  7. Tips and Reminders • R is case-sensitive • Comment your code so you remember what it does; comments are preceded with # • R scripts are simply text files with a .R extension • Use Ctrl + R to submit code • Use the Tab key to let R/R Studio finish typing commands for you • Use Shift + down arrow to highlight lines or blocks of code • In R Studio: Ctrl + 1 and Ctrl + 2 switches between script and console • Use up and down arrows to cycle through previous commands in console • Don’t be afraid of errors; you won’t break R • If you get stuck, Google is your friend

  8. Resources • Google • Web sites • UCLA IDRE: http://www.ats.ucla.edu/stat/r/ • Quick-R: http://www.statmethods.net/ • Rtips: http://pj.freefaculty.org/R/Rtips.html • Reference card: http://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf • Books • R Cookbook (Paul Teetor) • R in a Nutshell (Joseph Adler) • Coursera Classes • Computing for Data Analysis (Sept 23, 4 weeks) • Data Analysis (Oct 28, 8 weeks)

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