Undergraduate Course: Statistical Methods for Economics (ECNM08016)
Course Outline
| School | School of Economics |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 8 (Year 2 Undergraduate) |
Availability | Available to all students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | 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. |
| Course description |
Not entered
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Information for Visiting Students
| Pre-requisites | A knowledge of calculus and an Economics course taken previously, or permission of the course organiser. |
Course Delivery Information
| Not being delivered |
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.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Additional Class Delivery Information |
Two lectures per week each lasting 1 hour, one weekly 1.5 hour tutorial to be arranged in addition. |
| 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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