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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2014/2015
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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Theory of Statistical Inference (MATH10028)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) Credits10
Home subject areaMathematics Other subject areaSpecialist Mathematics & Statistics (Honours)
Course website https://info.maths.ed.ac.uk/teaching.html Taught in Gaelic?No
Course descriptionCourse 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.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Foundations of Calculus (MATH08005) AND Several Variable Calculus (MATH08006) AND Linear Algebra (MATH08007) AND Methods of Applied Mathematics (MATH08035) AND ( Probability (Year 2) (MATH08008) OR Probability (Year 3) (MATH09004)) AND ( Statistics (Year 2) (MATH08051) OR Statistics (Year 3) (MATH09021))
Co-requisites
Prohibited Combinations Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?Yes
Course Delivery Information
Delivery period: 2014/15 Semester 1, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 15/09/2014
Breakdown of 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 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Written Exam 95 %, Coursework 5 %, Practical Exam 0 %
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)2:00
Summary of Intended 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.
Assessment Information
See 'Breakdown of Assessment Methods' and 'Additional Notes', above.
Special Arrangements
None
Additional Information
Academic description Not entered
Syllabus Not entered
Transferable skills Not entered
Reading list Not entered
Study Abroad Not entered
Study Pattern Not entered
KeywordsTSI
Contacts
Course organiserDr Natalia Bochkina
Tel: 0131 650 8597
Email: 		Course secretaryMrs Alison Fairgrieve
Tel: (0131 6)50 5045
Email:
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