ECONOMIC DATA ANALYSIS - 2017/8
Module code: ECO1017
ARSENIS P Dr (Economics)
Number of Credits
FHEQ Level 4
Module cap (Maximum number of students)
Overall student workload
Independent Study Hours: 128
Lecture Hours: 22
Laboratory Hours: 10
|Assessment type||Unit of assessment||Weighting|
|Coursework||GROUP PROJECT PROPOSAL||20|
A take-home assignment can serve as an alternative assessment for the group project proposal for resitting students, or those with extenuating circumstances (weighted 20%) An individual project can serve as an alternative assessment for the group project for resitting students, or those with extenuating circumstances (weighted 80%).
Prerequisites / Co-requisites
Economics is a data-driven subject and figures on growth, unemployment, spending and inflation provide the raw material for many of the theories that dominate the subject. This module explores the data on which economics relies. Several lectures will be focused on understanding the data, but, also, discuss the measurement of key macroeconomic data series. The laboratory sessions will be focused on using the data, developing students understanding on examining and presenting data using Excel.
develop an understanding of how data are analysed;
familiriase with the measurement of economic indices and economic activity;
develop Excel skills.
|Be able to graphically and numerically examine data distributions.||CPT|
|Familiarise with the concept of density and the normal distribution.||K|
|Understand the concept of correlation and causation and be able to distinguish them.||KCPT|
|Use Excel to examine and present data.||CPT|
|Familiarise with the measurement of price level, GDP and economic growth.||K|
|Produce a written report using macroeconomic data describing its measurement and evolution over time using the skills learned in the module.||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
Indicative content includes:
Graphical and numerical examination of distributions;
Correlation, least-squares regression and causation;
Economic indices and measuring economic activity;
Using Excel to examine and present data.
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
enhance skills in information and data gathering, evaluation and written presentation
appreciate the complexities of decision making, weighing theory and practice
develop students IT skills so that they can competently analyse real data using a range of techniques.
The learning and teaching methods include:
2 hour lecture per week x 11 weeks + library sessions
1-hour drop-in feedback computer lab session
The assessment strategy is designed to provide students with the opportunity to demonstrate their skills in working with computers and associated communications and information technology. The assessment strategy for this module consists of a group project proposal in which the students set out basic aspects of their project (e.g. objectives, methodology etc.) and of a final group project in which the students will have to demonstrate their ability to use data analysis to examine issues in economics.
Thus, the summative assessment for this module consists of:
A group-based proposal to be submitted in semester week 8. The proposal should pin down the topic the students would like to investigate, the methodology they plan to adopt and the sources (literature and data) they intend to use. The assessment is designed to help the students structure their research idea and motivate them to start working on their project. 20% of the module mark is awarded for this assessment.
A final group (minimum 5 - maximum 6 students) report that is made available during the term and should be submitted after the Christmas break in January. Each group should use secondary data sources and the taught techniques to analyse a specific economic issue in depth. The assessment is designed to evaluate students’ ability to gather, analyse and interpret information on a particular issue and to use this knowledge to construct a critical written report. It also assesses students’ ability to work in a group and to reflect on the learning experience in undertaking a group based assessment. 80% of the module mark is awarded for this assessment.
The written report should be between 3,000 and 4,000 words in total (including tables, graphs and references). The report should provide a critical overview of a particular topic. Students are expected to define and discuss relevant economic concepts and to explain clearly how relevant data are measured or constructed. Graphical and numerical analyses should be undertaken as necessary.
Formative assessment and feedback
Students have weekly feedback sessions. For these, students are being provided with a set of exercises relating to the lecture material which they solve independently. In the feedback sessions, they receive feedback on their answers and guidance on how these answers could be improved. In addition to this, students receive solutions online. Moreover, the marked coursework scripts provide students with individual feedback on their learning and identify potential weaknesses to enhance their performance.
Reading list for ECONOMIC DATA ANALYSIS : http://aspire.surrey.ac.uk/modules/eco1017
Programmes this module appears in
|Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Economics and Finance BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
|Business Economics BSc (Hons)||1||Compulsory||A weighted aggregate mark of 40% is required to pass the module|
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2017/8 academic year.