Postgraduate Course: Statistical Modelling (MATH11039)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Available to all students |
| SCQF Credits | 5 |
ECTS Credits | 2.5 |
| Summary | 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. |
| Course description |
Week 1 - Goodness-of-fit tests
Week 2 - Multiple Regression
Week 3 - Multiple Regression / Model Building
Week 4 - Model Building
Week 5 - Logistic regression
|
Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Information for Visiting Students
| Pre-requisites | None |
| High Demand Course? |
Yes |
Course Delivery Information
|
| Academic year 2016/17, Available to all students (SV1)
|
Quota: None |
| Course Start |
Block 3 (Sem 2) |
Timetable |
Timetable |
| 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 )
|
| Assessment (Further Info) |
Written Exam
50 %,
Coursework
50 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
See 'Breakdown of Assessment Methods' and 'Additional Notes', above. |
| Feedback |
Not entered |
| Exam Information |
| Exam Diet |
Paper Name |
Hours & Minutes |
|
| Main Exam Diet S2 (April/May) | MSc Statistical Modelling | 1:30 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Ability to use statistical software to fit appropriate models and interpret associated 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.
|
Contacts
| Course organiser | Dr Vanda Fernandes Inacio De Carvalho
Tel: (0131 6)50 4877
Email: Vanda.Inacio@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
|
© Copyright 2016 The University of Edinburgh - 3 February 2017 4:43 am
|
University Homepage