To develop undergraduate students' research skills: students will have to work independently and find things out for themselves; To develop undergraduate students' computing skills: students will be taught how to generate pictures/diagrams and equations in word, to present data in tables and graphs in excel and be given an introduction to an advance statistical software package; To learn about data handling and data description; To learn relevant economic statistics and hypothesis testing: this module will include numerical work on microeconomic datasets, which is part of the basic training of every economist. The module forms part of the first year core cluster EC120 Quantitative Techniques, which is made up of one module in Mathematical Techniques (A (EC121) or B (EC123)), one module in Statistical Techniques (A (EC122) or B (EC124)) as well as Computing and Data Analysis (EC125).
Principal Learning Outcomes
By the end of the module the student should be able to use and undertake basic programming in the selected statistical software package; undertake basic cleaning of micro datasets and preliminary data description of those datasets; undertake basic statistical analysis and hypothesis testing of datasets; write reports of their data description and data analysis, distilling key insights and conclusions.
The module will typically cover the following topics:
Computing skills; Economic statistics; Descriptive statistics; Data awareness; Data analysis; Report-writing and report-presentation
- Core Module
- L100 - Year 1, LM1D (LLD2) - Year 1, V7ML - Year 1, L1L8 - Year 1, L116 - Year 1
- Pre or Co-requisites
- Pre-requisite for
- This module is restricted to L100, L116, LM1D/LLD2, V7ML students and L1L8 students on Route B.
- Part-year Availability for Visiting Students
- Not available on a part-year basis
- Assessment Method
- Coursework (100%)
- Coursework Details
- Two assignments: Assignment 1 (individual assignment) (10%) and Assignment 2 (Group project) (90%)
- Exam Timing