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There is a wealth of information out there to help anyone, from students to statisticians and everyone in between. The following resources are websites, text and articles, software, and miscellaneous stuff that I have found quite helpful. Slowly, yet steadily, I will add to these resources.



  • UCLA: Institute for Digital Research and Education. A great resource for online help with a variety of statistics problems, from concepts to applications of software, e.g. R, SAS, SPSS. This site offers plenty of examples of how to perform various analyses in multiple programs and how to interpret the results. I strongly recommend them.

  • Thesaurus of Mathematical Languages. A thesaurus of sorts that shows you common commands in one language in another, e.g. R commands and the corresponding commands for MATLAB users.


Text and Articles

  • The Art of R Programming. An online article provided by UC Davis, it is a nice starting package for figuring out how to use R. I strongly recommend taking a look at the text because, as I mention below, R does have a steep learning curve.

  • Dr. Andy Field has produced several texts on the topics of statistical software, including books on learning R, SAS, and SPSS. His series, Discovering Statistics is written beautifully, in common language, that all experience levels can utilize. If you go to his personal website, please do not be scared away by his idiosyncrasies.


Instructional Videos

  • Marin Stats Lectures. A great source of videos from Professor Michael Marin at the School of Population and Public Health, University of British Columbia. He has been teaching introductory statistics for more than 10 years and one of the best statistics professors at UBC.



  • The R Project for Statistical Consulting. Simply referred to as R, it is a free license statistical program that can perform a multitude of statistical tests. Admittedly it has a steep learning curve initially, as many people are not fans of syntax, i.e. typing in commands and submitting it to be ran by the program. Ignoring that fact, it is one of the best resources for statisticians that can be ran on Windows, Mac OS X, UNIX, Linux, and servers alike.

    • R Commander. A bypass for those not inclined to learn syntax, this plugin sets up a graphical user interface (GUI) to allow users a point-and-click interface. The best part? It will also show you the syntax code necessary to perform the tasks at hand.

    • R Studio. A powerful and productive user interface for R, it is another type of GUI for R but not to the extent of R Commander. Instead, it modifies the environment of R's interface. For those familiar with MATLAB, R Studio contains various windows for the commands, an editor, workspace, etc.


  • Freemat. A free license environment for rapid engineering and scientific prototyping and data processing that is "similar" to MATLAB and other commercial systems, such as IDL from Research Systems, that is free. FreeMat is available under the GPL license and supports windows, linux, and mac os x. UNIX environments, e.g. IRIX/SOLARIS, might be a bit dicey, so tread with caution.


  • PSPP. A program for statistical analysis of sampled data. It is a Free replacement for SPSS that is a stable and reliable application. It can perform descriptive statistics, T-tests, ANOVA, linear and logistic regression, measures of association, cluster analysis, reliability and factor analysis, non-parametric tests and more. Its back end is designed to perform its analyses as fast as possible, regardless of the size of the input data. You can use PSPP with its graphical interface or the more traditional syntax commands.

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