Bachelor of Science (BSc)

BSc Economics

Undertake highly structured training in economics, with a focus on enhancing and applying quantitative and analytical skills in modern economics.
  • Duration: 3 or 4 years
  • Year of entry: 2025
  • UCAS course code: L102 / Institution code: M20
  • Key features:
  • Study abroad
  • Industrial experience

Full entry requirementsHow to apply

Course unit details:
Applied Economics

Course unit fact file
Unit code ECON10162
Credit rating 10
Unit level Level 1
Teaching period(s) Semester 2
Available as a free choice unit? No

Overview

The course will provide an introduction how economists use data and statistics to deal with common economic problems. The aim is to allow students to perform economic analysis using real-world data and standard statistical packages. This will help prepare students for more advanced courses in econometrics and applied economics.

Pre/co-requisites

Available to BSc Economics students only

Available to BSc Economics students only

Aims

The aim of this module is to introduce students to the tools and techniques used in economics as a practical discipline. The course will provide an introduction to the ways in which economists use data and statistics to tackle economic problems, testing and interpreting economic theories. The aim is to allow students to perform economic analysis using real world data and standard statistical packages. This will help prepare students for more advanced courses in econometrics and applied economics. 

 

Learning outcomes

Students will learn how to:

1. Develop empirically testable hypotheses from economic theory.

2. Manipulate data in order to test interesting economic hypotheses.

3. Apply basic econometric methods to data.

4. Interpret empirical results derived from applying econometric methods to data.

5. Understand some of the limitations and potential pitfalls of empirical work in
     economics  

Students will have experience of using standard statistical computer packages as a research tool. They will have experience of report writing using appropriate information technology.

Syllabus

The course will cover the structure of data, exploratory data analysis, data visualization techniques, basic statistical methods, hypothesis testing and linear regression, among other data and statistical techniques. Strong emphasis will be placed on the practical element of applied work in problem solving, and the interpretation that can be given to empirical results. We will look at issues around various economic topics, such as: microeconomics, macroeconomics, labour market, inequalities, environmental issues, finance, etc. 

Teaching and learning methods

Synchronous activities (such as Lectures, Office hours, and tutorials), and guided self-study.

Employability skills

Group/team working
Oral communication
Problem solving
Research
Other
Enhances transferable skills including self-management and presentational skills.

Assessment methods

40% Weekly Quizzes

60% Written Project - 1500 words max 

Feedback methods

  • Online quizzes.
  • Tutorials classes.
  • Office hours
  • Revision sessions.
  • Discussion boards.

Recommended reading

The course will primarily draw on "The Art of Statistics: Learning from Data" by David Spiegelhalter.

May also refer to other textbooks, such as:

  • Wooldridge, J.M. (2013) Introductory Econometrics: A Modern Approach (University of Manchester custom edition).

Additional readings will be provided for various topics during the course.

Study hours

Scheduled activity hours
Lectures 25
Tutorials 10
Independent study hours
Independent study 65

Teaching staff

Staff member Role
Matheus Vianna Unit coordinator

Additional notes

For every 10 course unit credits we expect students to work for around 100 hours. This time generally includes any contact times, but also independent study, work for coursework, and group work. This amount is only a guidance and individual study time will vary.

 

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