Undergraduate Course: Statistics (Yr 3) (MATH09022)
Course Outline
| School | School of Mathematics |
College | College of Science and Engineering |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 9 (Year 3 Undergraduate) |
Credits | 10 |
| Home subject area | Mathematics |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | Syllabus summary: Summary 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. |
Information for Visiting Students
| Pre-requisites | None |
| 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
(
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
75 %,
Coursework
25 %,
Practical Exam
0 %
|
| 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
| See 'Breakdown of Assessment Methods' and 'Additional Notes' above. |
Special Arrangements
| None |
Additional Information
| Academic description |
Not entered |
| Syllabus |
Summary 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. |
| Transferable skills |
Not entered |
| Reading list |
Not entered |
| Study Abroad |
Not Applicable. |
| Study Pattern |
See 'Breakdown of Learning and Teaching activities' above. |
| Keywords | StaY3 |
Contacts
| Course organiser | Prof Colin Aitken
Tel: (0131 6)50 4877
Email: C.G.G.Aitken@ed.ac.uk |
Course secretary | Mrs Kathryn Mcphail
Tel: (0131 6)50 4885
Email: k.mcphail@ed.ac.uk |
|
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