autumn  2009,  7.5 points

Teachers  Literature  Examination  Assimilation  
FoPT Telegraph  

The course covers, i.a.,
*  Basics:
events and probabilities, measures, random variables and their distributions,  expectations
with a view towards the Lebesgue integral,  the first Borel-Cantelli lemma.

*  Independence and Conditioning:
conditional probabilities, the second Borel-Cantelli lemma, the strong law of large numbers, random walk and the Markov property.

*  Transforms:
probability generating functions, moment generating functions, Laplace transforms,
characteristic functions, Poisson approximation, the central
limit theorem.

Now when we have entered a new century, it seems appropriate that we have a course
at the Master level that covers the foundations of
probability theory that were laid after
the year 1900!                     

The book to be used is
Williams: Weighing the Odds (Cambridge University Press 2001).
It is available in paperback; the  plan is to take Chapters 1-5 and part of the first
section in Chapter 9 as a base for the course.  If you like to know more about the
author, click here:  Williams . On that home page, you also find a link to the book.

The course takes place in the second quarter of the academic year,
i.e., essentially November-December (until the Christmas break).
There will be three sessions a week,
two of them for lectures, and
one for classes, with exercises, examples, etc.

The  schedule looks as follows:

lectures: Mondays and Wendesdays, 10.00-11.45
classes: Mondays, 13.15-15.00

And the location is the same throughout:   MVF 26

But in the first week, the Monday (26 Oct.) sessions are cancelled!
They are replaced by a session on Tusday, 27 Oct.,  10.00-11.45 in MVF 31,
and one later, if needed. There are lectures only the first week.

See  you on Tuesday, 27 October, at. 10.00 in MVF31!

Torgny Lindvall   &   Marcus Warfheimer


Click here for some very influential people!

Two poineers of measure and integration theory:
H. Lebesgue        E. Borel      

and four dedicated to probability theory:
A. Khinchin     A. Kolmogorov    P. Lévy     J.  Doob