Durham University
Programme and Module Handbook

Undergraduate Programme and Module Handbook 2022-2023 (archived)

Module ECON1021: ECONOMIC METHODS

Department: Economics

ECON1021: ECONOMIC METHODS

Type Open Level 1 Credits 20 Availability Available in 2022/23 Module Cap Location Durham

Prerequisites

  • A level Maths, minimum grade A

Corequisites

  • Principles of Economics (ECON1011).

Excluded Combination of Modules

  • Calulus I (MATH1061), Singe Maths A (MATH1561), Maths for Engineers and Scientists (MATH1551).

Aims

  • To familiarise students with the use of mathematical and numerical tools in solving economic problems, and to provide a quantitative basis for progression to final honours. In addition, students will have the opportunity to develop key skills.

Content

  • Mathematical Section: Equations; Matrix algebra; Differential calculus; Integral calculus.
  • Statistical Section: Descriptive statistics; Probability, Probability distributions; Sampling distributions; Confidence intervals; Hypothesis tests; Introduction to regression analysis

Learning Outcomes

Subject-specific Knowledge:
  • an understanding of basic data analysis
  • an appreciation of the characteristics of economic data
  • a facility with the mathematical techniques of elementary algebra and optimisation
  • experience in using these techniques in economic model building and analysis
Subject-specific Skills:
  • The ability to set up basic economic problems as systems of mathematical equations and solve constrained optimisation resource allocation problems
  • To understand statistical distributions and basic hypothesis testing
Key Skills:
  • Written Communication -by completing the summatively-assessed project
  • Numeracy - e.g. by applying core mathematical and statistical skills to answer a range of examination questions
  • Problem Solving and Analysis - by applying the necessary mathematical and quantitative skills to a wide range of economic problems
  • Planning, Organisation and Time Management - by collecting and organising data for the statistical project and ensuring submission by the strict assignment deadline.
  • Initiative - e.g. by searching relevant literature and information in preparation for the project.
  • Computer Literacy and Information Retrieval -e.g. by the compulsory use of word processing and spreadsheets in the production of the summative project

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

  • Teaching is by lectures and tutorials. Learning takes place through attendance at lectures, preparation for and participation in tutorial classes, and private study. In addition, there are two optional computer practicals, and weekly drop-in sessions.
  • Summative assessment is by means of a written examination to test students knowledge and understanding of the subject-matter, plus a written assignment to test their ability to apply what they have learned.

Teaching Methods and Learning Hours

Activity Number Frequency Duration Total/Hours
Lectures 40 2 per week 1 hour 40
Revision Lectures 2 1 per week in term 3 1 hour 2
Seminars 10 1 every 2 weeks 1 hour 10
Computer practicals 2 2 in term 2 1 hour 2
Preparation and Reading 146
Total 200

Summative Assessment

Component: Examination Component Weighting: 80%
Element Length / duration Element Weighting Resit Opportunity
One written examination 2 hours 100% Same
Component: Assignment Component Weighting: 20%
Element Length / duration Element Weighting Resit Opportunity
Assignment 1500 100% Same

Formative Assessment:

Online test


Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University