THE UNIVERSITY of EDINBURGH

DEGREE REGULATIONS & PROGRAMMES OF STUDY 2013/2014

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Statistics (Yr 3) (MATH09022)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Course typeStandard AvailabilityAvailable to all students
Credit level (Normal year taken)SCQF Level 9 (Year 3 Undergraduate) Credits10
Home subject areaMathematics Other subject areaNone
Course website None Taught in Gaelic?No
Course descriptionSummary statistics, sampling distributions, hypothesis testing, interval estimation, likelihood, analysis of categorical data, joint, marginal and conditional distributions, ANOVA and regression. The computer program R will be introduced through a two-hour practical near the beginning of the course. Its use will be supported with examples in lectures and tutorials with supplementary material on the course website.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Probability (MATH08066)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Statistics (Year 2) (MATH08051)
Other requirements None
Additional Costs None
Information for Visiting Students
Pre-requisitesNone
Displayed in Visiting Students Prospectus?No
Course Delivery Information
Delivery period: 2013/14 Semester 2, Available to all students (SV1) Learn enabled:  Yes Quota:  None
Web Timetable Web Timetable
Course Start Date 13/01/2014
Breakdown of Learning and Teaching activities (Further Info) Total Hours: 100 ( Directed Learning and Independent Learning Hours 100 )
Additional Notes
Breakdown of Assessment Methods (Further Info) Please contact the School directly for a breakdown of Assessment Methods
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S2 (April/May)MATH09022 Statistics (Year 3)2:00
Resit Exam Diet (August)MATH09022 Statistics (Year 3)2:00
Summary of Intended Learning Outcomes
- Knowledge of common statistical procedures, and their implementation in a statistical package.
- Understanding of randomness and, in particular, sampling distributions.
- Ability to conduct simple inferential procedures and to exercise diagnostic and interpretative skills.
- Ability to interpret likelihood analyses.
- Facility with bivariate, marginal and conditional distributions.
- Ability to fit, criticise and predict from simple linear regression and one-way classification models.
- Ability to interpret test statistics and significance probabilities.
- Facility with the R statistical package for methods of inference developed in the course.
Assessment Information
Coursework 15%; examination 85%
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
KeywordsStaY3
Contacts
Course organiserProf Colin Aitken
Tel: (0131 6)50 4877
Email:
Course secretaryMrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email:
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