Undergraduate Course: Data Analysis (MATH10011)
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 10 (Year 4 Undergraduate) |
Credits |
20 |
Home subject area |
Mathematics |
Other subject area |
Specialist Mathematics & Statistics (Honours) |
Course website |
http://student.maths.ed.ac.uk |
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Course description |
Course for Honours Degrees involving Statistics.
The syllabus may change from year to year according to what other courses in Statistics are offered, but it is likely to contain most of the following topics.
1. Two-way and three-way classifications, blocking, interaction
2. Models with categorical and continuous variables, analysis of covariance
3. Generalized linear models for binary and count data
4. Repeated measures, emphasising the use of summary statistics
5. Discriminant analysis, especially Normal-based methods and logistic discrimination
6. Random effect models, emphasising REML estimation for Normal models
7. Non-linear regression
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Course Delivery Information
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Delivery period: 2010/11 Semester 1, Available to all students (SV1)
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WebCT enabled: Yes |
Quota: None |
Location |
Activity |
Description |
Weeks |
Monday |
Tuesday |
Wednesday |
Thursday |
Friday |
King's Buildings | Laboratory | | 1-11 | | | | 15:00 - 15:50 | | King's Buildings | Lecture | | 1-11 | | | 10:00 - 10:50 | | | King's Buildings | Laboratory | | 1-11 | | | | 16:10 - 17:00 | | King's Buildings | Lecture | | 1-11 | 15:00 - 15:50 | | | | |
First Class |
Week 1, Monday, 15:00 - 15:50, Zone: King's Buildings. JCMB, room 4312 |
Summary of Intended Learning Outcomes
1. Knowledge of S-Plus commands for plotting and annotation (including interaction plots and methods for repeated measures), fitting linear models, model selection, summarising multivariate data, discriminant analysis, variance component estimation and non-linear regression.
2. Ability to choose and apply appropriate statistical models and methods for the topics listed in the Syllabus Summary.
3. Ability to prepare typed reports of statistical analyses using LaTeX (or MS Word) and selected S-Plus output.
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Assessment Information
Coursework only.
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Please see Visiting Student Prospectus website for Visiting Student Assessment information |
Special Arrangements
Not entered |
Contacts
Course organiser |
Dr Liam O'Carroll
Tel: (0131 6)50 5070
Email: L.O'Carroll@ed.ac.uk |
Course secretary |
Mrs Alison Fairgrieve
Tel: (0131 6)50 6427
Email: Alison.Fairgrieve@ed.ac.uk |
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copyright 2010 The University of Edinburgh -
1 September 2010 6:18 am
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