Postgraduate Course: MIGSAA Statistics 1 (MATH12019)
Course Outline
School | School of Mathematics |
College | College of Science and Engineering |
Credit level (Normal year taken) | SCQF Level 12 (Postgraduate) |
Availability | Not available to visiting students |
SCQF Credits | 15 |
ECTS Credits | 7.5 |
Summary |
One aim is to introduce some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas. Another is to develop good computational skills using R, the statistical computing package which is in widespread use for statistical work in academia and industry. |
Course description |
- Introduction to R
- Review of linear models
- Likelihood methods (and optimisation)
- Review of generalised linear models
- Simulation and bootstrapping
- Case study
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Entry Requirements (not applicable to Visiting Students)
Pre-requisites |
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Co-requisites | |
Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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Academic year 2023/24, Not available to visiting students (SS1)
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Quota: None |
Course Start |
Semester 1 |
Timetable |
Timetable |
Learning and Teaching activities (Further Info) |
Total Hours:
150
(
Lecture Hours 20,
Programme Level Learning and Teaching Hours 3,
Directed Learning and Independent Learning Hours
127 )
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Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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Additional Information (Assessment) |
Coursework : 100% |
Feedback |
Not entered |
No Exam Information |
Learning Outcomes
Gain an introductory understanding of some key topics which lie at the heart of research in statistical methods and form a basis for more advanced and sophisticated ideas.
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Additional Information
Graduate Attributes and Skills |
Not entered |
Keywords | migsaa,statistics |
Contacts
Course organiser | Prof A Carbery
Tel: (0131 6)50 5993
Email: A.Carbery@ed.ac.uk |
Course secretary | Ms Isabelle Hanlon
Tel: (0131 6)50 5955
Email: i.hanlon@ed.ac.uk |
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