Module Details

Module Code: ECON7009
Title: Economic Data and Analysis
Long Title: Economic Data and Analysis
NFQ Level: Intermediate
Valid From: Semester 1 - 2024/25 ( September 2024 )
Duration: 1 Semester
Credits: 5
Field of Study: 3140 - Economics
Module Delivered in: 6 programme(s)
Module Description: The module aims to equip students with the necessary skills to assess and manipulate economic data in order to assist in business decision making. This is facilitated through the use of micro and macro level economic data.
 
Learning Outcomes
On successful completion of this module the learner will be able to:
# Learning Outcome Description
LO1 Describe techniques for collecting, managing and visualising economic data.
LO2 Interpret investment appraisal techniques.
LO3 Manipulate economic functions using Microsoft Excel to present and interpret data.
LO4 Forecast trend values using time series analysis.
Dependencies
Module Recommendations

This is prior learning (or a practical skill) that is strongly recommended before enrolment in this module. You may enrol in this module if you have not acquired the recommended learning but you will have considerable difficulty in passing (i.e. achieving the learning outcomes of) the module. While the prior learning is expressed as named MTU module(s) it also allows for learning (in another module or modules) which is equivalent to the learning specified in the named module(s).
20183 ECON7009 Economic Data and Analysis
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. You may not earn additional credit for the same learning and therefore you may not enrol in this module if you have successfully completed any modules in the incompatible list.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements

This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. You may not enrol on this module if you have not acquired the learning specified in this section.
No requirements listed
 
Indicative Content
Economics and Business Research Analysis Tools
Data concepts, how data supports decision making, data collection and management techniques, data visualisation. Data’s role in measuring progress towards SDGs and enabling sustainability.
Investment Appraisal
Discounting, net present values, internal rate of return of investment and cost benefit analysis with an emphasis on incorporating sustainability into investment decisions.
Economic Data Manipulation
Manipulate demand, supply and consumption functions using microsoft excel.
Economics and Business Forecasting
Analyse sales trends, prices and indices using microsoft excel and data visualisation.
Module Content & Assessment
Assessment Breakdown%
Coursework100.00%

Assessments

Coursework
Assessment Type Short Answer Questions % of Total Mark 40
Timing Week 7 Learning Outcomes 1,2
Assessment Description
For example, a written exam on data collection, data management and investment appraisal techniques.
Assessment Type Practical/Skills Evaluation % of Total Mark 60
Timing Week 13 Learning Outcomes 3,4
Assessment Description
For example, use forecasting techniques to analyse sales trends and use regression analysis to explore the relationship between economic variables.
No End of Module Formal Examination
Reassessment Requirement
Coursework Only
This module is reassessed solely on the basis of re-submitted coursework. There is no repeat written examination.

The University reserves the right to alter the nature and timings of assessment

 

Module Workload

Workload: Full Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of content and material underpinning learning outcomes Every Week 3.00 3
Lab Contact Lab based practical application Every Week 1.00 1
Independent & Directed Learning (Non-contact) Non Contact Student undertakes independent study including reading relevant course material Every Week 3.00 3
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 4.00
Workload: Part Time
Workload Type Contact Type Workload Description Frequency Average Weekly Learner Workload Hours
Lecture Contact Delivery of content and material underpinning learning outcomes Every Week 1.50 1.5
Lab Contact Lab based practical application Every Week 0.50 0.5
Independent & Directed Learning (Non-contact) Non Contact Student undertakes independent study including reading relevant course material Every Week 5.00 5
Total Hours 7.00
Total Weekly Learner Workload 7.00
Total Weekly Contact Hours 2.00
 
Module Resources
Recommended Book Resources
  • Les Oakshott. (2016), Essential Quantitative Methods, 7th Edition. Red Globe Press, p.0, [ISBN: 9781137518552].
Supplementary Book Resources
  • Wayne Winston. (2021), Microsoft Excel 365 Data Analysis and Business Modeling, 7th Edition. Microsoft Press, [ISBN: 9780137613663].
  • Gary Koop. (2013), Analysis of Economic Data, 4th Edition. John Wiley & Sons, p.277, [ISBN: 9781118472538].
  • James R. Evans. Business Analytics, 3rd Edition. [ISBN: 9780135231678].
This module does not have any article/paper resources
Other Resources
 
Module Delivered in
Programme Code Programme Semester Delivery
CR_BBUSS_7 Bachelor of Business 4 Mandatory
CR_BACCT_8 Bachelor of Business (Honours) in Accounting 4 Elective
CR_BIBLA_8 Bachelor of Business (Honours) in International Business with Language 4 Mandatory
CR_BACCT_7 Bachelor of Business in Accounting 4 Elective
CR_BBUSS_6 Higher Certificate in Business 4 Mandatory
CR_BACCT_6 Higher Certificate in Business in Accounting 3 Elective