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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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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 descriptionSimple Multiple Regression: Polynomial, qualitative, and interaction variables; heteroscedacity and weighted least squares; hypothesis tests concerning variables and groups of variables; stepwise regression and model selection. Forecasting Regression: Trend variables, seasonal binary variables, leading indicator variables, lagged dependent variables, and first order serially correlated errors; ex-sample forecasting; Durbin-Watson and related tests. Qualitative Dependent Variables: Discriminant analysis and logistic regression; application to credit scoring; hypothesis tests, confusion matrices, ROC curves, hold-out samples.
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, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 1, Directed Learning and Independent Learning Hours 37 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 100 %, Coursework 0 %, 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 estimate models using SPSS and EXCEL and to interpret output. Versatility in devising and assessing model structures. Knowledge of relationships adequate to calculate statistics and model outcomes.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
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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