Postgraduate Course: Generalised Regression Models (MATH11187)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||The course builds on the material covered in MATH10095 Statistical Methodology, extending the statistical techniques described to generalised linear models.
Topics to be covered include :
- generalised linear models;
- analysis of deviance;
- exponential families; and
- generalised linear mixed models.
Course Delivery Information
|Academic year 2018/19, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 22,
Seminar/Tutorial Hours 5,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 5%; Examination 95%
||Hours & Minutes
|Main Exam Diet S2 (April/May)|| Generalised Regression Models (MATH11187)||2:00|
On completion of this course, the student will be able to:
- Understand generalised linear models and their application to different problems.
- Understand mixed effects and their interpretations.
- Identify and apply appropriate statistical models to data and interpret the corresponding results.
- Use R to fit generalised linear models to data.
|An Introduction to Generalized Linear Models. Dobson and Barnett. Chapman and Hall.|
|Graduate Attributes and Skills
||These Postgraduate Taught courses may be taken by Undergraduate students *without* requiring a concession (NB. students on Postgraduate taught programmes are given priority in the allocation of places). For all other Postgraduate Taught courses the student and/or Personal Tutor must seek a concession.
|Course organiser||Dr Bruce Worton
Tel: (0131 6)50 4884
|Course secretary||Miss Gemma Aitchison
Tel: (0131 6)50 9268