Introduction to Statistics Using R



Day Date Topic Assignment
Mon Jan 9 Introduction  
Wed Jan 11 Probability  
Mon Jan 16 Hypothesis Testing  
Wed Jan 18 R Practical A01.pdf
Mon Jan 23 One Way ANOVA  
Wed Jan 25 R Practical  
Mon Jan 30 Multiple Comparisions & Statistical Power A02.pdf
Wed Feb 1 R practical with Andrew  
Mon Feb 6 R practical: multiple comparisons  
Wed Feb 8 Two and Three Factor ANOVA (read on your own, no class today) A03.pdf
Mon Feb 13 R practical: 2-way ANOVA  
Wed Feb 15 ANCOVA A04.pdf
Mon Feb 20 Family Day holiday—no class  
Wed Feb 22 reading week—Q&A / work (optional)  
Mon Feb 27 Q&A with Andrew (optional)  
Wed Mar 1 Q&A with Andrew (optional)  
Mon Mar 6 no class today  
Wed Mar 8 Multiple Regression A05.pdf
Mon Mar 13 Bootstrapping and Resampling Methods A06.pdf
Wed Mar 15 R practical  
Mon Mar 20 Maximum Likelihood Estimation (MLE)  
Wed Mar 22 R practical  
Mon Mar 27 Bayesian Approaches A07.pdf
Wed Mar 29 R practical  
Mon Apr 3 Bayesian Approaches  
Wed Apr 5 Q&A (optional)  

Other Topics

Notes in pdf format

Psychology 9041B

  • Instructor: Paul Gribble
  • email: paul [at] gribblelab [dot] org
  • office: NSC 228
  • lab: NSC 245G
  • Course TA: Andrew Vo (avo6 [at] uwo [dot] ca)
  • class schedule: Mondays & Wednesdays, 1:30pm–2:30pm
  • class location: PAB 150
  • first class: Monday January 9, 2017
  • course website: http://www.gribblelab.org/stats



  • Designing Experiments and Analysing Data: A Model Comparison Perspective (2nd Edition) by Scott E. Maxwell & Harold D. Delaney. Lawrence Erlbaum Associates (2003). ISBN: 0805837183 [ buy it at amazon.com ]
  • Design and Analysis: A Researcher's Handbook (4th Ed.) by Geoffrey Keppel. Prentice Hall (2004). ISBN: 0135159415
  • A Beginner's Guide to R by Zuur, Ieno & Meesters. Springer (2009). ISBN: 9780387938363 [ buy it at amazon.com ] [ read it online ] [ code & data ]
  • R for Data Science by Hadley Wickham & Garrett Grolemund. O'Reilly (2017). ISBN: 978-1491910399 [ buy it at amazon.com ] [ read it online ]

Online Resources


  • Please submit all assignments using OWL: https://owl.uwo.ca
  • All assignments should be submitted as an R Notebook (a single .Rmd file)
  • Grading scheme:
    • 0: did not submit
    • 1: major corrections
    • 2: minor corrections
    • 3: no corrections


Do you have ideas about how to improve this course? Please get in touch, send me an email at paul [at] gribblelab [dot] org

Paul Gribble | Winter, 2017
This work is licensed under a Creative Commons Attribution 4.0 International License
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