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DRPS : Course Catalogue : School of Mathematics : Mathematics

Postgraduate Course: Statistical Methods (MATH11070)

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 Credits15 ECTS Credits7.5
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. It is the intention that the course will be available to postgraduate students on other programmes who would benefit.

This course is delivered by Heriot Watt University and is only available to students on the MSc Financial Mathematics programme.
Course description Data summary
Random variables, special distributions.
Multivariate distributions and linear combinations.
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 Inference (MATH11129)
Other requirements MSc Financial Mathematics students only.
Course Delivery Information
Academic year 2017/18, Not available to visiting students (SS1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 150 ( Lecture Hours 33, Seminar/Tutorial Hours 11, Summative Assessment Hours 3, Programme Level Learning and Teaching Hours 3, Directed Learning and Independent Learning Hours 100 )
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 Methods (MATH11070)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
- perform basic probability calculations
- find/calculate moments and expected values of random variables and functions of random variables; use generating functions
- 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
Main Texts:
John E Freund's Mathematical Statistics: (7th Ed.), Miller & Miller, Prentice-Hall
New Cambridge Statistical Tables: (2nd Ed.), Lindley & Scott, C.U.P.
Formulae and Tables for Examinations of the The Faculty of Actuaries and the Institute of Actuaries, 2002

Other Texts:
Introduction to Probability Theory and Statistical Inference: (3rd Ed.), H.J.Larson, Wiley
Introduction to Probability and Statistics: (8th Ed.), W. Mendenhall and R.J.Beaver, PWS, Kent
Essential Statistics (4th or later edition):Rees, Chapman and Hall/CRC
Additional Information
Graduate Attributes and Skills Not entered
Course organiserDr David Siska
Tel: (0131 6)51 9091
Course secretaryMs Hannah Burley
Tel: (0131 6)50 4885
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