MA30363: Modelling with randomness
[Page last updated: 22 May 2025]
Academic Year: | 2025/26 |
Owning Department/School: | Department of Mathematical Sciences |
Credits: | 6 [equivalent to 12 CATS credits] |
Notional Study Hours: | 120 |
Level: | Honours (FHEQ level 6) |
Period: |
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Assessment Summary: | EXOB 100% |
Assessment Detail: |
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Supplementary Assessment: |
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Requisites: |
Before taking this module you must take MA22016 OR take MA20221
In taking this module you cannot take MA30257 |
Learning Outcomes: |
* Identify real-world systems which are appropriately described in terms of stochastic models. * Formulate and analyse stochastic models using appropriate mathematical techniques. * Describe in mathematical terms the connections and differences between a range of stochastic methods, and between stochastic and deterministic modelling. * Analyse stochastic methodologies and associated analytical techniques. |
Synopsis: | In this unit you will study the application of stochastic models to understand real-world systems. You will explore a broad range of techniques. You will focus on analysing, understanding and interpreting the stochastic processes, rather than on rigorous theory. This unit will give you a different perspective on applied maths that is relevant to many sciences including biology, physics and finance. |
Content: | Stochastic modelling of chemical reactions: well-stirred systems; Gillespie algorithm; chemical master equation; analysis of simple systems; deterministic vs. stochastic modelling; systems with multiple favourable states; stochastic resonance; stochastic focusing; moment closure approximations for systems of one and two dependent variables. Examples of models of real-world stochastic systems. Stochastic differential equations: numerical methods; Fokker-Planck equation; first exit time; backward Kolmogorov equation; chemical Fokker-Planck equation. |
Course availability: |
MA30363 is Optional on the following courses:Department of Mathematical Sciences
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Notes:
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