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) |
Availability | Available to all students |
SCQF Credits | 10 |
ECTS Credits | 5 |
Summary | 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 |
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 |
High Demand Course? |
Yes |
Course Delivery Information
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Academic year 2015/16, Available to all students (SV1)
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Quota: None |
Course Start |
Semester 1 |
Timetable |
Timetable |
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 )
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Assessment (Further Info) |
Written Exam
95 %,
Coursework
5 %,
Practical Exam
0 %
|
Additional Information (Assessment) |
Coursework 5%, Examination 95% |
Feedback |
Not entered |
Exam Information |
Exam Diet |
Paper Name |
Hours & Minutes |
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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 | |
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Academic year 2015/16, Part-year visiting students only (VV1)
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Quota: None |
Course Start |
Semester 2 |
Timetable |
Timetable |
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% |
Feedback |
Not entered |
No Exam Information |
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 | Mr Brett Herriot
Tel: (0131 6)50 4885
Email: |
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© Copyright 2015 The University of Edinburgh - 27 July 2015 11:34 am
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