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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2015/2016

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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
Credit level (Normal year taken)SCQF Level 11 (Postgraduate) AvailabilityNot available to visiting students
SCQF Credits7.5 ECTS Credits3.75
SummaryThis 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 only available to MSc Financial Mathematics students.
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 2015/16, 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


Reading List
None
Additional Information
Graduate Attributes and Skills Not entered
KeywordsStIn
Contacts
Course organiserDr Sotirios Sabanis
Tel: (0131 6)50 5084
Email:
Course secretaryMr Brett Herriot
Tel: (0131 6)50 4885
Email:
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