Postgraduate Course: Statistical Inference (MATH11129)
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 | 7.5 |
ECTS Credits | 3.75 |
| Summary | This 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.
This course is delivered by Heriot Watt University and is only available to students on the MSc Financial Mathematics programme. |
| Course description |
- 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
|
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. |
Course Delivery Information
|
| Academic year 2018/19, Not available to visiting students (SS1)
|
Quota: None |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| 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 Information (Learning and Teaching) |
Examination takes place at Heriot-Watt University.
|
| Assessment (Further Info) |
Written Exam
100 %,
Coursework
0 %,
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) | Statistical Inference (MATH11129) | 2:00 | |
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
|
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | StIn |
Contacts
| Course organiser | Dr David Siska
Tel: (0131 6)51 9091
Email: D.Siska@ed.ac.uk |
Course secretary | Miss Sarah McDonald
Tel: (0131 6)50 5043
Email: sarah.a.mcdonald@ed.ac.uk |
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