Module Descriptors
PROBABILITY MODELS
MATH40210
Key Facts
Faculty of Computing, Engineering and Sciences
Level 4
15 credits
Contact
Leader: Emily Raeburn
Email: E.Raeburn@staffs.ac.uk
Hours of Study
Scheduled Learning and Teaching Activities: 36
Independent Study Hours: 114
Total Learning Hours: 150
Assessment
- ASSIGNMENT weighted at 50%
- EXAMINATION - UNSEEN IN EXAMINATION CONDITIONS weighted at 50%
Module Details
Module Resources
Excel/SPSS
Module Texts
For background reading only, e.g.
Grinstead & Snell, 1997. Introduction to Probability, AMS, ISBN: 0821807498
Sheldon M. Ross, 2003. Probability Models, Academic Press, ISBN: 0125980612
Grinstead & Snell, 1997. Introduction to Probability, AMS, ISBN: 0821807498
Sheldon M. Ross, 2003. Probability Models, Academic Press, ISBN: 0125980612
Module Learning Strategies
Learning Strategies.
Students are required to commit to 150 learning hours of which 36 hours will consist of contact time. Typically there will be 12 hours of lectures and 24 hours of tutorial/practical time. Lectures will provide students with a broad overview of the indicative content and the tutorial/practical sessions will allow students to practise the material covered in the lectures through problem solving. Learning support material will be provided.
Students are required to commit to 150 learning hours of which 36 hours will consist of contact time. Typically there will be 12 hours of lectures and 24 hours of tutorial/practical time. Lectures will provide students with a broad overview of the indicative content and the tutorial/practical sessions will allow students to practise the material covered in the lectures through problem solving. Learning support material will be provided.
Module Additional Assessment Details
An individual assignment requiring the use of probabilistic techniques to solve a range of problems. Use of appropriate software is also required. (Learning outcomes 1, 2, 3).
An examination weighted at 50% covering the overall content of the module (Learning outcomes 1, 2, 3, 4).
An examination weighted at 50% covering the overall content of the module (Learning outcomes 1, 2, 3, 4).
Module Indicative Content
Probability rules and Bayes' Theorem
Decision making techniques
Solve probability problems using standard statistical distributions such as Binomial, Poisson, Normal and Exponential.
Model univariate and bivariate discrete random variables using appropriate probability distributions.
Hypothesis testing including goodness of fit tests.
Decision making techniques
Solve probability problems using standard statistical distributions such as Binomial, Poisson, Normal and Exponential.
Model univariate and bivariate discrete random variables using appropriate probability distributions.
Hypothesis testing including goodness of fit tests.
Module Special Admissions Requirements
Disqualified combination: CE62023-2 Probability & Statistical Modelling.