Postgraduate Course: Statistical Theory (MATH11085)
Course Outline
| 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 |
| SCQF Credits | 10 |
ECTS Credits | 5 |
| Summary | - Statistical modelling and motivation.
- Parametric families and likelihood. Sufficiency, Neyman factorisation, minimal sufficiency, joint sufficiency. Elements of statistical decision theory.
- Estimation, minimum variance unbiased estimators, Cramer-Rao lower bound, Bayes and minimax estimators. Stein phenomenon and James-Stein estimator.
- Hypothesis testing, pure significance tests, optimal tests, power, Neyman-Pearson lemma, uniformly most powerful tests.
- Confidence intervals, relationship to hypothesis testing.
- Selected topics in modern statistics |
| Course description |
Not entered
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | Knowledge of mathematics, probability and statistics equivalent to passing the School of Mathematics' courses MATH08063 Several Variable Calculus and Differential Equations, MATH08066 Probability, and MATH08051 Statistics (Year 2). |
Course Delivery Information
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| Academic year 2016/17, 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:
100
(
Lecture Hours 22,
Seminar/Tutorial Hours 6,
Summative Assessment Hours 2,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
68 )
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| Assessment (Further Info) |
Written Exam
95 %,
Coursework
5 %,
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 S1 (December) | MATH11085 Statistical Theory | 2:00 | |
Learning Outcomes
On completion of this course, the student will be able to:
- Knowledge of the theory of statistical inference.
- Ability to prove and apply results concerning statistical inference.
- Ability to develop theoretical arguments.
- Familiarity with dealing with multiparameter statistical problems.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | STh |
Contacts
| Course organiser | Dr Jonathan Gair
Tel: (0131 6)50 4897
Email: J.Gair@ed.ac.uk |
Course secretary | Mrs Frances Reid
Tel: (0131 6)50 4883
Email: f.c.reid@ed.ac.uk |
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