cogmaster-stats

This course is a short and practical introduction to statistical analysis of experimental data.

• We will not cover mathematical statistics, but we will focus on applied statistics.
• We will not provide a complete account of statistical modeling.
• Examples will come from various disciplines: experimental psychology, medicine, biomedical engineering.
• We will try to emphasize the interpretation of results, and how to get them right.

• Time: 9:00–11:30, every Tuesday
• Prerequisites: basic math and experimental design
• Statistical packages: R (sessions 1 to 6), Python (sessions 7 to 10)
• Resources: Handouts available on Github, open access textbook
• Homeworks: short exercices to complete at home
• Grading: 50% assignements, 50% final project

Website: http://cogmaster-stats.github.io/site

Christophe Lalanne [R], Sylvain Charron and Gaël Varoquaux [Py].

1. Working with Data (Oct. 8)
2. Descriptive statistics, two-group comparisons (Oct. 15)
3. ANOVA and design of experiments (Oct. 22)
4. More advanced ANOVA (Oct. 29)
5. Linear regression (Nov. 5)
6. Other regression models (Nov. 12)

Sessions 7 to 10 with Python will be detailed later.

• R software: http://www.r-project.org/
• RStudio: http://www.rstudio.com/
• An HTML viewer: Chrome, Firefox, Safari, Internet Explorer (not tested)

R slides and handouts are written using RStudio. You will have access to the full code, and you are encouraged to review it before the course.

Note: To compile the HTML slides, you will need the Preview version of RStudio.