Generalized Linear Models. Spring 2004

Many problems in data analysis can be reduced to Generalized Linear Models. These models will be introduced, and many of the common applications will be dicussed. The focus will be on the practical aspects of model building and data analysis. Prerequisites: Probability theory, statistical inference, Linear models. Credits: 3ov.

The decision about having linear models as a pre-requisite was taken before the timetable was changed, so anyone taking Mervi Eerola's course on linear models at the same time should be OK.

More information will be given later, but if you insist on knowing more, email me.

Time and place: March 9th - April 29th

• Tuesdays, 16.00-18.00
• Thursdays, 16.00-18.00 (sorry)

NOTE: The lectures will start at precisely 16.00, not 16.15. This means we can finish slightly earlier.

Seminar room of RNI (Ylionpistokatu 5, take the lifts next to Alko to the 7th floor, turn right).

Lectures by Doc. Bob O'Hara.

Lecture Notes (added when I've completed them!)

• Lecture 1
• Lecture 2
• Problems Set 1
• Lecture 3
• Lecture 4: Computer Practical
• Problems Set 2
• Data for problems Set 2
• Lecture 5
• Lecture 6
• Problems Set 3
• Data for problems Set 3
• Lecture 7
• Lecture 8
• Problems Set 4
• Data for problems Set 4: Bumpus.txt
• Data for problems Set 4: Eggs.txt
• Lecture 9
• Lecture 10
• Lecture 11
• Problems Set 5
• Lecture 12
• Problems Set 6
• Data for problems Set 6: roads.txt
• Lecture 13
• Lecture 14
• Problems Set 7
• Data for problems Set 7: mice.txt
• Data for problems Set 6: Fiji.txt