Undergraduate Course: Statistical Methods for Economics (ECNM08016)
Course Outline
| School | School of Economics |
College | College of Humanities and Social Science |
| Course type | Standard |
Availability | Available to all students |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Credits | 20 |
| Home subject area | Economics |
Other subject area | None |
| Course website |
None |
Taught in Gaelic? | No |
| Course description | The course is intended as an introduction to probability theory and statistics for economists and other social science students. Basic concepts, sample spaces, events, probabilities; Conditioning and independence, Bayes' formula; Discrete random variables, expectation, variance, mean, independence; Continuous random variables, distributions and densities; Jointly distributed random variables, joint distribution functions, independence and conditional distributions; Covariance, correlation, conditional expectation, moment generating functions; Law of large numbers (strong and weak), central limit theorem; Summary statistics; Sampling distributions; Hypothesis testing; Interval estimation; ANOVA and regression. Excel 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. |
Information for Visiting Students
| Pre-requisites | A knowledge of calculus and an Economics course taken previously, or permission of the course organiser. |
| Displayed in Visiting Students Prospectus? | No |
Course Delivery Information
| Not being delivered |
Summary of Intended Learning Outcomes
Understanding of the basic notions of Probability
Understanding of conditional probability and independence.
Familiarity with discrete and continuous probability distributions.
Ability to work with some random variables, and calculate their expected values.
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 fit, criticise and predict from simple linear regression and one-way classification models.
Ability to interpret test statistics and significance probabilities.
General skills developed include: critical analysis and assessment; reasoning adaptably and systematically; problem-framing and problem-solving skills; basic numeracy and quantitative skills; obtaining and processing information from a variety sources; presentation and communication skills; computer and IT skills; independent action and initiative; managing tasks and time; coping with stress. |
Assessment Information
Mid-semester (MCQ) examination: 20%
December Exam: 80%
- Tutorial attendance: Tutorial penalty 6 marks deducted for 4 missed tutorials, 8 marks deducted for 5 missed tutorials, 10 marks deducted for 6 missed tutorials, 12 marks deducted for 7 missed tutorials, 14 marks deducted for 8 missed tutorials, 18 marks deducted for 9 missed tutorials.
Resit Exam (August diet): 100%
Visiting Student Assessment
As 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 |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Ahmed Anwar
Tel: (0131 6)50 8355
Email: Ahmed.Anwar@ed.ac.uk |
Course secretary | Ms Dawn Mcmanus
Tel: (0131 6)50 6946
Email: Dawn.McManus@ed.ac.uk |
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