Unit name | Economic Data |
---|---|
Unit code | EFIM10016 |
Credit points | 20 |
Level of study | C/4 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Dr. Hans Sievertsen |
Open unit status | Not open |
Pre-requisites |
None |
Co-requisites |
EFIM10009 Mathematical and Statistical Methods 2 |
School/department | School of Economics |
Faculty | Faculty of Social Sciences and Law |
This unit focuses on obtaining, processing and presenting numerical economic information. The unit will introduce students to ways of accessing statistical databases from National Statistical Agencies, International Organizations, and other publicly available data sources. The students will learn concepts that are important for understanding and presenting economic data in a non-misleading way, for example the definition of GDP, price-indices, survey weights and log-scales. The unit will also introduce students to various ways to present the processed data (verbally, tables, graphs), and how to decide what presentation method to use. The students will be shown how to perform basic analyses of data using software packages such as MS Excel.
Topics covered will include
The unit will draw on links that the department has with the Office for National Statistics.
Students will be able:
Large-group teaching (“Lectures”): a total of 18 hours to deliver the material
Small-group teaching in computer labs (“Classes”): 9 one-hour classes of groups of circa 15-20 students
Revision and additional lectures: 2 hours for revision and supplementary material (sometimes in enhancement week)
No significant e-learning components are envisaged at the moment, but the department is experimenting with additional teaching methods to improve the student learning experience.
Formative Assessment
Formative assessment will consist of problem-solving and data-analysis questions, marked by the class tutor and returned with feedback.
In line with the department’s policy of augmenting traditional formative assessment with electronic assessment, formative assessment may be supplemented with small online quizzes or other electronic resources.
Summative Assessment
This will be a project to analyse economic data. The maximum project length will be 15 pages. This assesses all of the learning outcomes.
Schwabish, Jonathan A. 2014. "An Economist's Guide to Visualizing Data." Journal of Economic Perspectives, 28(1): 209-34. DOI: 10.1257/jep.28.1.209
Stephen Few: “Show Me the Numbers”, Analytics Press; 2nd New edition (30 Jun. 2012)
Edward R. Tufte: “The Visual Display of Quantitative Information”, Graphics Press USA; 2nd edition (31 Jan. 2001) (optional)