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Department of Mathematics

Probability Models (G1100)

Probability Models

Module G1100

Module details for 2022/23.

15 credits

FHEQ Level 6

Module Outline

Short revision of probability theory

Expectation and conditional expectation

Convergence of random variables, in particular laws of large numbers, moment generating functions, central limit theorem.

Stochastic processes in discrete time in particular Markov chains, including random walk, martingales in discrete time, Doob's optional stopping theorem, martingale convergence theorem.

Module learning outcomes

Setting up probability spaces, events and random variables to solve real-life probability problems.

Manipulating distributions, densities, sums of random variables, basic random processes and Markov chains with applications.

Understanding and using the Laws of Large Numbers and the Central Limit Theorem, with an eye to statistics and probability modelling.

Acquire and rediscover set-theoretical and calculus skills in the context of probabilistic manipulations.

TypeTimingWeighting
Computer Based ExamSemester 1 Assessment80.00%
Coursework20.00%
Coursework components. Weighted as shown below.
PortfolioT1 Week 11 40.00%
Problem SetT1 Week 5 15.00%
Problem SetT1 Week 10 15.00%
Problem SetT1 Week 8 15.00%
Problem SetT1 Week 3 15.00%
Timing

Submission deadlines may vary for different types of assignment/groups of students.

Weighting

Coursework components (if listed) total 100% of the overall coursework weighting value.

TermMethodDurationWeek pattern
Autumn SemesterLecture2 hours11111111111
Autumn SemesterLecture1 hour11111111111

How to read the week pattern

The numbers indicate the weeks of the term and how many events take place each week.

Dr Vladislav Vysotskiy

Assess convenor
/profiles/406081

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