Postgraduate Course: Statistical Modelling (MATH11039)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Course type | Standard |
Availability | Not available to visiting students |
Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Credits | 5 |
Home subject area | Mathematics |
Other subject area | Operational Research |
Course website |
http://student.maths.ed.ac.uk |
Taught in Gaelic? | No |
Course description | Goodness-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: 2014/15 Block 4 (Sem 2), Available to all students (SV1)
|
Learn enabled: Yes |
Quota: None |
|
Web Timetable |
Web Timetable |
Course Start Date |
23/02/2015 |
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 Modelling | 2:00 | |
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 |
Keywords | STAM |
Contacts
Course organiser | Dr Julian Hall
Tel: (0131 6)50 5075
Email: J.A.J.Hall@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
|
© Copyright 2014 The University of Edinburgh - 29 August 2014 4:21 am
|