Courses / Module

• Describe and discuss the foundations and key results of modern probability and information theory in an integrated format.
• Describe contemporary applications of probability.
• Pursue independent research in these topics.

• The module will consist of 24 hours of lectures and 96 hours of independent study.

• Module Graded (numeric value) or Ungraded (Pass/Not Passed): Ungraded
• Other detail(s): Two hour in-house written examination

• Could the result of this module be capped? No
• Less than 40% - did not complete; between 40% and 100% - pass

• Are supplemental/resit registrations permitted? No

• Registered PhD student; Advanced Calculus; Basic Linear Algebra; some knowledge of real analysis and basic probability

• None

P. Billingsley,

“Probability and Measure'', third edition. Wiley (1995).

[Wiley series in probability and mathematical statistics]

J. S. Rosenthal,

“A first look at rigorous probability theory'',

second edition. World Scientific (2006).

Y. Suhov and M. Kelbert,

“Probability and Statistics by Example'', Volume 1, Basic Probability and Statistics Cambridge University Press (2005)

T. M. Cover and J. A. Thomas,

“Elements of Information Theory'',

second edition. Wiley (2006).

This timetable is not currently available, please contact the Hamilton Institute Department.