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

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

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: 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 )
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.