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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014 -
- ARCHIVE as at 1 September 2013 for reference only
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Statistical Inference (MATH11129)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityNot available to visiting students
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) Credits7.5
Home subject areaMathematics Other subject areaNone
Course website None Taught in Gaelic?No
Course descriptionThis course aims to provide postgraduate students with a broad knowledge of the principal areas of mathematical statistics and statistical methods widely used in actuarial science and finance. Students should have a good grounding in probability before commencement of this course.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Co-requisites
Prohibited Combinations Students MUST NOT also be taking Statistical Methods (MATH11070)
Other requirements MSc Financial Mathematics students only.
Additional Costs None
Course Delivery Information
Delivery period: 2013/14 Semester 1, Not available to visiting students (SS1) Learn enabled:  No Quota:  None
Web Timetable Web Timetable
Course Start Date 16/09/2013
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 75 ( Lecture Hours 15, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 56 )
Additional Notes Examination takes place at Heriot-Watt University.
Breakdown of Assessment Methods (Further Info) Written Exam 100 %, Coursework 0 %, Practical Exam 0 %
No Exam Information
Summary of Intended Learning Outcomes
On completion of this course the student should be able to:
- demonstrate knowledge of, and a critical understanding of, statistical methodologies (including the main concepts and methods of inference and modelling)
- understand and apply a range of statistical techniques based on the main theories and concepts which comprise the syllabus, including the central limit theorem
- determine properties of estimators: efficiency, Cramer-Rao lower bound, (approx.) large sample distributions of MLEs
- perform inference on parameter estimates, including constructing confidence intervals and testing hypotheses on the values of parameters
- fit a linear regression model and critically evaluate other proposed models; test hypotheses concerning correlation coefficients
- show an awareness of how different statistical models and techniques can be applied to financial problems
- communicate meaningfully and productively with others (including practitioners and professionals in the financial services industry and elsewhere) on matters relating to and/or requiring the use of statistical methods


Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
MSc Financial Mathematics students only.
Additional Information
Academic description Not entered
Syllabus - Sampling distributions, central limit theorem, t and F distributions
- Estimation - properties of estimators, methods of constructing estimators
- Interval estimation
- Hypothesis testing
- Linear relationships - regression and correlation
Transferable skills Not entered
Reading list Not entered
Study Abroad Not Applicable.
Study Pattern Not entered
KeywordsStIn
Contacts
Course organiserDr Sotirios Sabanis
Tel: (0131 6)50 5084
Email: S.Sabanis@ed.ac.uk
Course secretaryMrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: k.mcphail@ed.ac.uk
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