Undergraduate Course: Theory of Statistical Inference (MATH10028)

Course Outline
School	School of Mathematics	College	College of Science and Engineering
Credit level (Normal year taken)	SCQF Level 10 (Year 4 Undergraduate)	Availability	Available to all students
SCQF Credits	10	ECTS Credits	5
Summary	Course for final year students in Honours programmes in Statistics. Parametric families and likelihood. Sufficiency, Neyman factorisation, minimal sufficiency, joint sufficiency, Bayesian sufficiency. Estimation, minimum variance unbiased estimators, Cramr-Rao lower bound, Bayes estimators. Hypothesis testing, pure significance tests, optimal tests, power, Neyman-Pearson lemma, uniformly most powerful tests. Confidence intervals, relationship to hypothesis testing, Bayesian credible intervals. Bayesian inference, conjugate prior distributions, predictive distributions.
Course description	Not entered

Entry Requirements (not applicable to Visiting Students)
Pre-requisites	Students MUST have passed: ( Several Variable Calculus and Differential Equations (MATH08063) AND Fundamentals of Pure Mathematics (MATH08064) AND Probability (MATH08066)) AND ( Statistics (Year 2) (MATH08051) OR Statistics (Yr 3) (MATH09022))	Co-requisites
Prohibited Combinations		Other requirements	None

Information for Visiting Students
Pre-requisites	None

Course Delivery Information

Academic year 2015/16, Available to all students (SV1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 )
Assessment (Further Info)	Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Additional Information (Assessment)	Coursework 5%, Examination 95%
Feedback	Not entered
Exam Information
Exam Diet	Paper Name		Hours & Minutes
Main Exam Diet S1 (December)	MATH10028 Theory of Statistical Inference		2:00

Academic year 2015/16, Part-year visiting students only (VV1)		Quota: None
Course Start	Semester 1
Timetable	Timetable
Learning and Teaching activities (Further Info)	Total Hours: 100 ( Lecture Hours 22, Seminar/Tutorial Hours 5, Summative Assessment Hours 2, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 69 )
Assessment (Further Info)	Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Additional Information (Assessment)	Coursework 5%, Examination 95%
Feedback	Not entered
No Exam Information

Learning Outcomes
1. Knowledge of the theory of statistical inference. 2. Ability to prove and apply results concerning Frequentist and Bayesian inference. 3. Ability to develop theoretical arguments. 4. Familiarity with dealing with multiparameter problems.