Dear all,
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)