Graduate Course in Principal Component Analysis (PCA)

General Information

Principal component analysis (PCA) is a powerful tool in, for example, experimental sciences, where the goal is to evaluate the effect of a set of (many) variables. PCA often provides a tool to descibe experimental variation in significantly fewer variables than the original physical problem.

Preliminary course plan

Date Chapter Lecturer
t.b.d. Ch. 1 & 2 Johan C.
t.b.d. Ch. 3 t.b.d.
t.b.d. Ch. 4 t.b.d.
t.b.d. Ch. 5 t.b.d.
t.b.d. Ch. 6 t.b.d.
t.b.d. Ch. 7 t.b.d.
t.b.d. Ch. 8 t.b.d.
t.b.d. Ch. 9 t.b.d.
t.b.d. Ch. 10 t.b.d.
t.b.d. Ch. 11 t.b.d.
t.b.d. Ch. 12 t.b.d.
t.b.d. Ch. 13 t.b.d.
t.b.d. Ch. 14 t.b.d.
t.b.d. Article presentations t.b.d.
t.b.d. Article presentations t.b.d.
t.b.d. Article presentations t.b.d.

Examination

Basic requirements (4p)

To pass the course and gain 4 points, the following requirements must be fulfilled:

For one extra course point

To receive one extra point, the student must present a plan of how to use the presented methods in his/her own research. Written report with detailed plans, also summarizing the theory of the methods to be used.
Senast ändrad: 2004-10-14, av Johan Carlson