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Code & Analyze the Data

Coding, Analysis, and Statistical Computing

Now that you have your data, it's time for coding, cleaning, transforming, and, eventually, analysis. This can be a tricky and frustrating process for beginners and experts alike, particularly if you're working with a new software program. We hope that this page will ease your pain and enable you to do amazing things with the information you collected.

Here you'll find information on how to access statistical software on and off campus and resources for data analysis in some of the most common statistical software programs.

Accessing Statistical Software at AU

AU students, faculty, and staff have open access to a number of statistical packages on and off campus.

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  • Campus Computers

    • If you're working on a campus computer that is logged on to the AU network, your already have access to SPSS, Stata, and EViews through the U: drive.
    • Stata, SPSS, EViews, and SAS are also installed natively on the machines in all of AU's computing labs. Some labs also include software for managing and analyzing "big data." Find out more at the Campus Computing Facilities page.
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    Virtual Computing

    • On or off campus, access more than 10 different statistical software packages (including StatTransfer) and your AU Network drives through American University's Virtual Computing Lab, VCL. Read more about the VCL and how to access it from your personal computer at the VCL website.

    Learning to Use Statistical Software

    Below you will find a brief list of tutorials and video guides to four of the most common statistical software packages.  

    In addition to these resources, note that there are hundreds of books on each program (many of them available for check out at the AU Library). Moreover, there are very few data questions that have not been asked and answered online. A simple search will typically help you solve even the most advanced challenges. 

    Finally, note that consultants at the Center for Teaching, Research, and Learning (CTRL) offer both regular software workshops and drop-in hours for AU students, faculty, and staff. You can find their schedule at the CTRL Lab webpage.

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    Stata

    Microsoft Excel

    • Lynda.com Excel playlist
    • Follow the link above to a playlist with introductory and intermediate courses on using Excel for statistical analysis. You will need your AU login information to access this site.
    • Beginner's Guide
    • This e-book is a guide for "absolute beginners" with Excel. It is available through the AU library. You will need your AU login information to access it.
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    IBM SPSS

    • Lynda.com SPSS playlist
    • A free course on statistical computing using IBM SPSS. You will need your AU login information to access this course.
    • UCLA Stat Consulting Group
    • Explore the guides, videos, and annotated output. You will find resources for SPSS users at all levels.
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    R and Python

    • Lynda.com R and Python resources
    • Here you'll find introductory courses on using R and Python languages for statistical computing and programming. Use your AU login information to access the courses.
    • UCLA Stat Consulting Group
    • This is a great place to explore the R environment for users at all levels. You'll find guides for beginners, annotated output, and technical discussions for advanced programmers.
    • An R Introduction
    • A written introduction to the open-source R environment. First-time users may want to start with the information in Appendix A of this guide.
    • Quick-R Guide
    • This open and extensive site provides an excellent introduction to R, especially for those looking to transition to R from other statistical software packages.