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Curricular information is subject to change
On the completion of this module the student should be familiar with the fundamental concepts of probability theory. This includes probability measures, random variables, independence, expectation, modes of convergence, laws of large numbers, central limit theorem, conditional expectation, martingales, Brownian motion. The student will develop their ability to deal with abstract concepts and to relate them to concrete examples. The student's ability to realise and critique proofs and arguments will be enhanced.
Indicative Module Content:Probability and measure; laws of large numbers; central limit theorem; conditional expectation; martingales; introduction to Brownian motion.
Student Effort Type | Hours |
---|---|
Lectures | 36 |
Autonomous Student Learning | 72 |
Total | 108 |
Students are strongly recommended to revise Introduction to Probability (STAT20110) and Measure Theory & Integration (MATH30360) prior to commencing the course.
Resit In | Terminal Exam |
---|---|
Autumn | Yes - 2 Hour |
• Group/class feedback, post-assessment
Not yet recorded.
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 | Fri 13:00 - 14:50 |
Lecture | Offering 1 | Week(s) - 20, 21, 22, 23, 24, 25, 26, 29, 30, 31, 32, 33 | Thurs 16:00 - 16:50 |