QUANTitative Analysis & Statistics: Statistical Software

Mason provides SPSS and SAS for faculty computers, but does not provide any software licenses for student computers. Students can instead use Patriot Virtual Computing & Labs to get access to all standard statistical software. However, many people prefer when the software is on their own computer.

For Theses, Dissertations, and other >1 semester projects, it is important to be able to replicate all your actions from the beginning. The best way to do this is by saving the computer syntax to perform actions.

• If you used Qualtrics to collect data, consider whether it alone is sufficient for analysis
  • Basic one-variable graphs - See Results
  • Simple Qualitative coding/tagging - See Text IQ
  • Examining Relationships: Results with Breakouts, and Cross Tabs  (despite the name, It can also do t-tests)
• If you just need to do one or two statistical tests, check out the Statistics Calculators in the other box. 
• If you learned Stata or SAS AND you feel comfortable with it, use that.
  • The Virtual Lab works fine for Stata, but learn how to save and access files to be efficient.
  • SAS offers OnDemand for Academics for free online, or you can use the Virtual Lab
  • You can also consider the free language R, and there are many tutorials specifically about switching.
• If you learned SPSS
  • If you feel confident with it and will [learn to] use Syntax, it is a fine choice. If you only need to do bivariate analyses, the free PSPP may be sufficient, otherwise you should purchase the grad pack. 
  • Otherwise, consider the free Jamovi, but do consider your ability to replicate from the beginning and make use of the features it has to ensure your project will be so.
• If you learned Excel and/or you are not comfortable with computers, consider  the free Jamovi.
  • If you have a Windows computer, you could use use Excel's Power Query for data management, as it is possible to redo and edit the actions.
  • If you really want to use Excel, use the Table and Pivot Table functions.
    • Note that it is not necessary to use numbers to represent categories (just type the category name consistently).
• Otherwise, consider the free R.

• Statistical Software Comparison by NYU Data Services
• Statistical Language Wars infographic from DataCamp Blog
• The Popularity of Data Analysis Software

• Stats Kingdom
  • Standard introductory tests, plus additional fit tests, sample size calculators, and regressions including multinational logistic. 
  • Often includes explanations, assumption tests, graphs, r code and a basic writeup in APA style.
• Social Science Statistics
  • Standard introductory tests, plus confidence intervals, linear and multiple regressions, and additional correlation tests.
  • Sister site of EZ SPSS Tutorials
• VassarStats
  • Standard introductory and multivariate tests for clinicians, plus more ANOVAs and, Simple Logistic Regression
  • See also Richard Lowry's online textbook Concepts & Applications of Inferential Statistics
• Effect Size Calculator
  • Calculate d, r, v, OR, RR, and CI's from the output of almost any test
  • Companion to the book Practical Meta-Analysis (see more Meta-Analysis Stuff) by David B Wilson, GMU

(Software-inclusive) A practically-focused book covering a basic multi-level model through generalized linear mixed models, with a comparison of and then complete example for each software.

These materials from experience researchers, some created years ago, are on sites with many old and/or broken links. But they contain gems on some topics that may not be found elsewhere.

• Karl L. Wuensch - Downloadable tutorials of varying length on graduate-level topics in Psychology. To fix most links, take out "psych/" from the URL Searching is best, but here are direct/correct links to: Statistics Lessons, Statistical Help, SAS Lessons, SPSS lessons (using search), and Research Design

• Jason T. Newsom - Gives examples in SPSS and R. See  his old Stats Notes plus handouts and slides for current courses including: Univariate Quantitative Methods, Multiple Regression and Multivariate Quantitative Methods, Categorical Data Analysis, Structural Equation Modeling (also Mplus and lavaan), Multilevel Regression (also HLM) and Measurement.