I have made a preliminary contents plan for the course as seen below. This is by no means not cut in stone, I will be happy to consider suggestions from students. We will discuss details on Lecture 1, but you are also welcome to (and encouraged to!) drop me an email prior to that, to let me know about your expectations and fields of interest.
The contents of the course will primarily evolve around Chapters 11-15 of the Milton & Arnold book, with particular focus on the Multiple linear regression model, Factorial experiments and Analysis of variance. Matrix algebra will be used to a large extent throughout the course, and I plan to devote 1-2 lectures on important matrix concepts (matrix multiplication, spectral decomposition, matrix inverse, projections, trace etc) and distributional properties of linear and quadratic forms.
I urge all students to attend Lecture 1 so that we can discuss and decide on the format and contents of the course together.
Preliminary plan of lectures:
Lecture 1. Introduction to the course, Matrix algebra I
Lecture 2. Matrix algebra II, quadratic forms
Lecture 3. Correlation, causality, data generating mechanisms, OLS and ML
Lecture 4. The multiple linear regression model, I
Lecture 5. The multiple linear regression model, II
Lecture 6. The multiple linear regression model, III
Lecture 7. Analysis of variance
Lecture 8. Factorial experiments
Lecture 9. Categorical data
Lecture 10. The R-software
Lecture 11. Extra, if needed
Lecture 12. Examination (presentations, discussions, oral exam)
- Kursansvarig: Thomas Holgersson