Curated Resources

The following is a list of references and resources selected by individuals affiliated with PMC on a variety of commonly encountered topics. Please e-mail Dr. Sigal if you come across a link that would be beneficial to add to this list!

Quantitative Methods and Affiliated Resources at Simon Fraser University

• The History, Quantitative, and Theorerical program at SFU
• The PMC mailing list
• The Statistical Consulting Service from the SFU Statistics Department

General Statistical Resources

• APA Task Force Report on Quantitative Psychology 
• Tutorials in Quantitative Methods for Psychology (online journal)
• Online Statistics (An Interactive Multimedia Course of Study)
• David Garson's StatNotes - Topics in Multivariate Analysis
  
• The Khan Institute's Videos on Statistical Theory
• StatSoft's Electronic Statistics Textbook
• The Division of Evaluation, Measurement, & Statistics (APA Division 5)
• The Sage Series on Quantitative Applications in the Social Sciences

Data Visualization

• Dr. Michael Friendly's DataVis.ca
  
• The Flowing Data blog
• AniWiki - Animations in Statistics
• SpatialAnalysis - A blog on spatial data visualization, analysis and other resources
• Computational History
  
• Jim Vallandingham's Data Visualization Posts
• Gestalt Principles for Data Visualization

Statistical Computing

• Statistical Computing at UCLA
• R Project for Statistical Computing
  
• Data Demystified - A YouTube video series on learning SPSS 
• Awesome R - Compilation of fantastic R resources
• Quick-R - An R blog for SAS and SPSS converts.
  
• R-Bloggers - An aggregate site that trolls a huge array of blogs devoted to working with R
  
• Revolutions - A blog about R and General Statistical Topics
• Show Me Shiny - Gallery of R Web Applications
  
• Shiny Dashboards - Interface for structuring Shiny GUIs
• Shiny Themes - Gallery of Shiny Customizations
• The SAS Training Post
  
• SAS Online Documentation
  
• Online Probability Calculators at StatTrek.com (for instance, from the binomial distribution)
• Introductory tutorials and tips for learning R can also be found at r4stats.com
• hackr.io - Tutorials for programming
  

Recommended Reading

• Flora, D. (2018). Statistical Methods for the Social and Behavioural Sciences: A Model-Based Approach. Sage.
  
• Friendly, M., & Meyer, D. (2016). Discrete Data Analysis with R: Visualization and Modeling Techniques for Categorical and Count Data. Chapman and Hall/CRC.