Statistical Foundations

This course is an introduction to statistics at a graduate level (generally PhD students take this course in preparation for further statistical training). Discussion includes topics such as data visualization, exploratory data analysis, and statistical tests (t-tests, ANOVA). This course uses R and RStudio for all data analyses.

Syllabus

Resources

• A PDF with all the formulas we use in the class.
• A PDF with all the tables we use in the class.

Slides

• Intro to the Class (PDF), Intro to the Textbook (PDF), APA Style Review (PDF), Getting Started with R, RStudio, and Latex (HTML), and Chapter 1 (HTML)
• Chapter 2 (PDF) or Chapter 2 (HTML)
• Chapter 3 (PDF) or Chapter 3 (HTML)
• Chapter 4 (PDF) or Chapter 4 (HTML)
• Chapter 5 (PDF) or Chapter 5 (HTML)
• Chapter 6 (PDF) or Chapter 6 (HTML)
• Chapter 7 (PowerPoint)
• Chapter 8 (PDF) or Chapter 8 (PowerPoint)
• Chapter 9 (PDF) or Chapter 9 (HTML)
• Chapter 10 (PDF) or Chapter 10 (HTML)
• Chapter 11 (PDF) or Chapter 11 (PowerPoint)
• Chapter 12 (PDF) or Chapter 12 (PowerPoint)
• Chapter 13 (PDF) or Chapter 13 (PowerPoint)
• Chapter 14 (PDF) or Chapter 14 (PowerPoint) and Chapter 14 Example (PDF) or Chapter 14 Example (PowerPoint)
• Chapter 15 (PDF) or Chapter 15 (PowerPoint)
  • An R Example of RM ANOVA HTML or RMD
• Chapter 16 (PDF) or Chapter 16 (PowerPoint)
  • An R Example of Mixed ANOVA HTML or RMD
• Chapter 19-20 (PDF) or Chapter 19-20 (PowerPoint)