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Curricular information is subject to change
An ability to understand the origins and development of probability theory. An ability to appropriately use many of the classic discrete probability distributions. An ability to calculate and manipulate probabilities given additional information.
Indicative Module Content:Topics covered will include: outcomes, events, and probability; independence; discrete random variables and distributions; expected value, moments and variance; permutations and combinations; binomial, multinomial and Poisson distributions; conditional probability and expectation.
Student Effort Type | Hours |
---|---|
Lectures | 24 |
Tutorial | 10 |
Autonomous Student Learning | 72 |
Total | 106 |
Not applicable to this module.
Resit In | Terminal Exam |
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Spring | Yes - 2 Hour |
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
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Mr Ganesh Babu | Tutor |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Fri 15:00 - 15:50 |
Lecture | Offering 1 | Week(s) - Autumn: All Weeks | Tues 10:00 - 10:50 |
Tutorial | Offering 1 | Week(s) - 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 | Fri 14:00 - 14:50 |
Tutorial | Offering 2 | Week(s) - 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 | Wed 14:00 - 14:50 |