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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 and continuous probability distributions. An ability to calculate and manipulate probabilities given additional information. An appreciation and ability to use the law of averages and the central limit theorem.
Indicative Module Content:Topics covered will include: outcomes, events, and probability; independence; random variables (both continuous and discrete) and distributions; expected value, moments and variance; permutations and combinations; binomial, multinomial and Poisson distributions; conditional probability and expectation; law of averages; central limit theorem.
Student Effort Type | Hours |
---|---|
Lectures | 36 |
Tutorial | 10 |
Autonomous Student Learning | 72 |
Total | 118 |
Desirable to already have taken a basic course in Statistics and be familiar with integration and differentiation.
Description | Timing | Component Scale | % of Final Grade | ||
---|---|---|---|---|---|
Continuous Assessment: Exercise sheets | Throughout the Trimester | n/a | Standard conversion grade scale 40% | No | 30 |
Examination: Written examination | 2 hour End of Trimester Exam | No | Standard conversion grade scale 40% | No | 70 |
Resit In | Terminal Exam |
---|---|
Spring | Yes - 2 Hour |
• Group/class feedback, post-assessment
Not yet recorded.
Name | Role |
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Iuliia Promskaia | Tutor |