Instructor: Nick Barton, Laszlo Erdös
Teaching Assistant: Harald Ringbauer
The concept of probability is fundamental to many scientific disciplines; understanding probability is important for modelling and data analysis, as well as for its intrinsic mathematical interest. This course teaches the basic principles by using a variety of examples, from computer science through to biology:
I. Basic Probability: history, definitions, applications
II. Discrete and Continuous Probability: random variables, distributions, statistics.
III. Stochastic Processes: random walks, Brownian motion, diffusion.
IV. Threshold Phenomena: branching, random graphs.
|Dec 2||Counting & Probability||LE|
|Dec 7||Conditional probability||LE|
|Dec 9||Random Variables I||NB|
|Dec 14||Random Variables II||NB|
|Dec 16||** Statistics Symposium|
|Jan 11||Random walk||NB|
|Jan 13||Branching processes||NB|
|Jan 20||Brownian motion||LE|
|Jan 25||Statistical physics||LE|
Problem Sheet 1 (due on December 14th)
Problem Sheet 2 (due on January 13th)
Problem Sheet 3 (due on January 25th)
The course roughly follows the schedule of last year. Accompanying material including expanded lecture notes can be found here. Most of the topics from this year are covered in these notes.