Undergraduate Course: Linear Statistical Modelling (MATH10005)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 10 (Year 3 Undergraduate) |
| Course type | Dissertation |
Availability | Available to all students |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Taught in Gaelic? | Yes |
| Summary description | Core course for Honours Degrees involving Statistics; optional course for Honours degrees involving Mathematics. Syllabus summary: Simple linear regression, relationships between variables, transformations to linearity, residual and regression sums of squares, analysis of variance and residual analysis. Multiple regression, matrix notation, distributions of sums of squares, inferences about regression parameters, and analysis-of-variance models. Use of R for statistical analysis. |
| Course description |
A basic familiarity with computing and IT is important for most careers and, increasingly, for many aspects of everyday life. This is reflected in business management and accounting, where computing resources are widely used as a source of information and a tool for word-processing, data analysis, and communication. This course gives background knowledge which will prove essential as students undertake further courses and proceed into the workplace.
Simple linear regression, relationships between variables, transformations to linearity, residual and regression sums of squares, analysis of variance and residual analysis.
Multiple regression, matrix notation, distributions of sums of squares, inferences about regression parameters, and analysis-of-variance models.
Use of R for statistical analysis.
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Information for Visiting Students
| Pre-requisites | None |
Course Delivery Information
|
| Delivery period: 2014/15 Semester 1, Available to all students (SV1)
|
Quota: None |
Timetable |
Timetable |
| Course Start Date |
15/09/2014 |
| Learning and Teaching activities (Further Info) |
Total Hours:
100
(
Lecture Hours 22,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
69 )
|
| Assessment (Further Info) |
Written Exam
95 %,
Coursework
5 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Coursework 5%, Examination 95% |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | Linear Statistical Modelling (MATH10005) | 2:00 | | | Main Exam Diet S1 (December) | Linear Statistical Modelling (For visiting students only) | 2:00 | |
Summary of Intended Learning Outcomes
1. Familiarity with simple linear regression and multiple linear regression.
2. Knowledge of the definition and properties of the Normal Linear Model.
3. Familiarity with some examples of the Normal Linear Model and ability to recognise other special cases.
4. Ability to use R for data analysis, particularly regression analysis and analysis of variance.
5. Ability to interpret the results of statistical analyses.
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Reading List
| http://www.readinglists.co.uk |
Contacts
| Course organiser | Dr Bruce Worton
Tel: (0131 6)50 4884
Email: |
Course secretary | Mrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: |
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