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.

Entry Requirements (not applicable to Visiting Students)
Pre-requisites	Students MUST have passed: Several Variable Calculus and Differential Equations (MATH08063) AND Fundamentals of Pure Mathematics (MATH08064) AND Probability (MATH08066) AND Statistics (Year 2) (MATH08051)	Co-requisites
Prohibited Combinations		Other requirements	None

Information for Visiting Students
Pre-requisites	None
High Demand Course?	Yes

Course Delivery Information

Academic year 2015/16, Available to all students (SV1)		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 )
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
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

Academic year 2015/16, Part-year visiting students only (VV1)		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.