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EC125: Computing and Data Analysis

  • Jeremy Smith

    Module Lecturer
  • Thomas Martin

    Module Lecturer
6 CATS - Department of Economics

Principal Aims

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


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

Reading Lists