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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Statistical Modelling (MATH11039)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits5
Home subject areaMathematics Other subject areaOperational Research
Course website http://student.maths.ed.ac.uk Taught in Gaelic?No
Course descriptionGoodness-of-fit tests: parametric using chi-squared test, non-parametric using Kolmogorov-Smirnov and graphical using probability plots. Multiple regression: continuous response and continuous explanatory variables, model diagnostics, continuous response and discrete-explanatory variables, continuous response and mixed continuous and discrete explanatory variables. Model building: variable selection, stepwise regression and multicollinearity. Logistic regression with binary response variable and continuous explanatory variables. The statistical software package SPSS will be used for practical instruction.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Course Delivery Information
Delivery period: 2013/14 Block 4 (Sem 2), Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 24/02/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 50 ( Lecture Hours 10, Supervised Practical/Workshop/Studio Hours 6, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 1, Directed Learning and Independent Learning Hours 31 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)MSc Statistical Modelling2:00
Summary of Intended Learning Outcomes
Ability to use SPSS to fit models and interpret output. Versatility in the development and assessment of model structures. Ability to calculate statistics and model outcomes. Response variables may be continuous or binary and explanatory variables may be discrete or continuous.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Week 1 - Goodness-of-fit tests
Week 2 - Multiple Regression
Week 3 - Multiple Regression / Model Building
Week 4 - Model Building
Week 5 - Logistic regression
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsSTAM
Contacts
Course organiserDr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk
Course secretaryMrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk
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