Course description

This course teaches analysis of balanced experimental designs with fixed, random, crossed, and nested factors; factorial, nested, nested factorial, split plot, split block, and repeated measures designs; and fixed and mixed effects models, residual analysis, and post hoc mean comparisons. Additional coursework is required for those enrolled in the graduate-level course.

PREREQ: Earn a minimum grade of C- one of the following:

Additional Course Information:


Class notes

  1. Software tutorials and installation (R + RStudio)
  2. Introduction
  3. Randomization and Hypothesis Testing
  4. Completely Randomized Design
  5. Factorial Designs
  6. Random Effects Models
  7. General Mixed Effects Models
  8. Designs with Nested Factors
  9. Block Designs

Homework and participation assignments

Please read the grading rubric before submitting homework.


Midterm

TODO: Specify midterm time


Final Exam

TODO: Update.


Acknowledgements and License

This course and the code involved are made available with an MIT license. A list of acknowledgments is available.