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| Module Availability |
All Year |
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| Assessment Pattern |
| Unit(s) of Assessment |
Weighting Towards Module Mark (%)
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| 2.5 Hour Examination |
70 |
| Coursework |
30 |
Qualifying Condition(s)
A weighted aggregated mark of 40% is required to pass the module. |
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| Module Overview |
This module initially covers descriptive statistics and exploratory data analysis and then concentrates on probability and statistical inference thus enabling students to undertake empirical work. The emphasis is on applications rather than mathematical rigour. |
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| Prerequisites/Co-requisites |
None |
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| Module Aims |
- To develop good data handling skills
- To understand the role statistical inference plays in economic analysis
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| Learning Outcomes |
| By the end of the module students will:-
be proficient in data presentation through computational methods
Have a good understanding of probability concepts including both discrete and continuous probability distributions;
Be able to construct and interpret confidence intervals;
Be able to formulate and conduct hypothesis tests for a wide range of applications |
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| Module Content |
The following is an indication of the likely topics to be covered:-
- Descriptive statistics - graphical presentation and summary measures of central tendency, dispersion and skew.
- Probability - mutually exclusive, independent and dependent events: Binomial, Poisson, Normal , t and Chi-squared distributions.
- Statistical inference - random samples; sampling distributions; confidence intervals and hypothesis testing.
- Covariance and correlation
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| Methods of Teaching/Learning |
Lectures (24 hrs) and classes (12 hrs) |
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| Selected Texts/Journals |
Lind, Marchal & Wathen. Basic Statistics for Business & Economics, 7th ed. McGraw Hill 2010
Anderson, Sweeney, Williams, Freeman & Shoesmith. Statistics for Business and Economics, Thompson. 2007
Crawshaw & Chambers, Concise Course in Advanced Level Statistics, 4th ed. Nelson Thomas, 2001 |
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| Last Updated |
27 September 2010
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