Introduction to Statistics Using R
Schedule
| 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
Books
- 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
- swirl: teaches you basic R programming, right in the console
- from Software Carpentry:
- Programming with R
- R For Reproducible Scientific Analysis (RStudio, dplyr, and ggplot2 lessons here)
- Getting started with RMarkdown
- ggplot2: a plotting system for R, based on the grammar of graphics
- Data Manipulation in R with dplyr
- Data Analysis and Visualization Using R: a course that combines video, HTML and interactive elements to teach R
Assignments
- 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
Ideas?
Do you have ideas about how to improve this course? Please get in touch, send me an email at paul [at] gribblelab [dot] org
