Welcome to the web pages for MAS371 Applied Probability. Course notes, exercises and solutions will appear here, in PDF format.

Face to face teaching has been suspended. Video lectures can be found via MOLE/Blackboard.

**Assessment** is by an exam at the end of the module. Details on how this will work during the COVID19 pandemic will follow.

**Feedback** will be via homeworks handed in on three occasions; provisionally, the deadlines will be the Thursdays in weeks 4, 7 and 10 (5 March, 26 March, 7 May).

Slides will appear here after the relevant section has been lectured.

- Slides for section 1 (Introduction)
- Slides for section 2 (Review of probability models)
- Slides for section 3 (Ideas and methods)
- Slides for section 4 (Inference for discrete time chains)
- Slides for section 5 (Continuous time chains)
- Slides for section 6 (Poisson processes)

Some exploration of further use of continuous time Markov chain models for epidemics, including some simulations, is available: Modelling an epidemic on a network.

Booklet of exercises for the course. This covers the whole course.

Solutions will appear here.

Solutions. All solutions are now available.

- R function for powers of matrices
- R function for calculating the spectral representation of a matrix
- R function for creating transition matrix for random walk on a triangle (question 6)
- R function for calculating W statistic for independence model (page 32)
- R code for Lake Constance analysis in chapter 6 and data

These will appear on MOLE before the exam. The exam papers themselves can be found on the SoMaS past papers page.

To contact the lecturer, email jonathan.jordan@sheffield.ac.uk.

A discussion board for this module is available on MOLE/Blackboard.

My home page

School of Mathematics and Statistics current students page

Last updated 14 May 2020.