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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2010/2011
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Likelihood (Ord) (MATH09008)

Course Outline
School School of Mathematics College College of Science and Engineering
Course type Standard Availability Available to all students
Credit level (Normal year taken) SCQF Level 9 (Year 3 Undergraduate) Credits 10
Home subject area Mathematics Other subject area Specialist Mathematics & Statistics (Ordinary)
Course website http://student.maths.ed.ac.uk Taught in Gaelic? No
Course description Syllabus summary: Likelihood function and exponential family. Likelihood based inference, score, Wald and likelihood ratio tests, and related confidence regions. Maximum likelihood, iterative estimation and Fisher's method of scoring. Generalized linear models, estimation, analysis of deviance, residuals, log linear and logistic linear models.
Entry Requirements
Pre-requisites Students MUST have passed: Foundations of Calculus (MATH08005) AND Several Variable Calculus (MATH08006) AND Linear Algebra (MATH08007) AND Methods of Applied Mathematics (MATH08035) AND Probability (Year 2) (MATH08008) AND Statistical Methods (MATH08009) AND Statistical Models (Year 2) (MATH08011)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Likelihood (MATH10004)
Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisites None
Displayed in Visiting Students Prospectus? Yes
Course Delivery Information
Not being delivered
Summary of Intended Learning Outcomes
The following are the learning objectives for the Honours version, MAT-3-Lik; for this (Ordinary) version there is more emphasis on the technical, rather than conceptual elements, which will be reflected by a different examination.

1. Familiarity with likelihood based inference.
2. Ability to apply likelihood methods to derive estimates, confidence intervals and hypothesis tests.
3. Familiarity with examples of generalized linear models, including Poisson regression and logistic regression.
4. Ability to use S-PLUS for statistical modelling and data analysis.
5. Ability to analyse data and interpret results of statistical analyses.
Assessment Information
Coursework: 15%; Degree Examination: 85%.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
Keywords Not entered
Contacts
Course organiser Dr Bruce Worton
Tel: (0131 6)50 4884
Email: Bruce.Worton@ed.ac.uk
Course secretary Mrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: k.mcphail@ed.ac.uk
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copyright 2011 The University of Edinburgh - 13 January 2011 6:20 am