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Degree Regulations & Programmes of Study 2010/2011
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Statistical Models (Year 2) (MATH08011)

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 08 (Year 2 Undergraduate) Credits 10
Home subject area Mathematics Other subject area Specialist Mathematics & Statistics (Year 2)
Course website http://student.maths.ed.ac.uk
Course description Core second year course for Honours Degrees including Statistics.

Syllabus summary: Modelling of data; one-way analysis of variance; simple linear regression; parametric families of distributions; likelihood; maximum likelihood estimation; likelihood ratio tests and intervals; joint, marginal and conditional distributions.
Entry Requirements
Pre-requisites It is RECOMMENDED that students have passed Probability (Year 2) (MATH08008) AND Statistical Methods (MATH08009)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Statistical Models (Year 3) (MATH09005)
Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisites None
Prospectus website http://www.ed.ac.uk/studying/visiting-exchange/courses
Course Delivery Information
Delivery period: 2010/11 Semester 2, Available to all students (SV1) WebCT enabled:  Yes Quota:  0
Location Activity Description Weeks Monday Tuesday Wednesday Thursday Friday
King's BuildingsLecture1-11 14:00 - 14:50
King's BuildingsLecture1-11 14:00 - 14:50
First Class First class information not currently available
Additional information Tutorials: one of Th 1500-1550, 1610-1700, Fr 1000-1050, 1110-1200
Summary of Intended Learning Outcomes
1. Facility with bivariate, marginal and conditional distributions.
2. Ability to fit, criticise and predict from simple linear regression and one-way classification models.
3. Ability to derive likelihood functions with one or two parameters, to plot one-parameter likelihoods, find their maxima and their curvature at maxima.
4. Ability to interpret test statistics and significance probabilities.
5. Ability to derive inferential methods using general procedures such as likelihood ratios and maximum likelihood.
6. Facility with Minitab commands for methods of inference developed in the course.
Assessment Information
Coursework: 15%; Degree Examination: 85%.
Please see Visiting Student Prospectus website for Visiting Student Assessment information
Special Arrangements
Not entered
Contacts
Course organiser Mr Michael Prentice
Tel: (0131 6)50 4876
Email: M.Prentice@ed.ac.uk
Course secretary Mr Martin Delaney
Tel: (0131 6)50 6427
Email: Martin.Delaney@ed.ac.uk
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copyright 2010 The University of Edinburgh - 1 September 2010 6:17 am