Skip to main content

Unit information: Quantitative Methods 2: Introduction to Statistics and Econometrics in 2014/15

Please note: you are viewing unit and programme information for a past academic year. Please see the current academic year for up to date information.

Unit name Quantitative Methods 2: Introduction to Statistics and Econometrics
Unit code ECON12122
Credit points 20
Level of study C/4
Teaching block(s) Teaching Block 2 (weeks 13 - 24)
Unit director Mr. Winter
Open unit status Not open
Pre-requisites

A-level Mathematics (or equivalent) ECON11122 Quantitative Methods 1

Co-requisites

None

School/department School of Economics, Finance and Management
Faculty Faculty of Social Sciences and Law

Description including Unit Aims

This unit is taught in two parts. In the first part, which will be covered in the Autumn Term, the fundamental ideas of mathematical statistics will be studied. Some of you may have been introduced to these ideas in your A level work.

Understanding the fundamental ideas of mathematical statistics is essential for much of your later work in Economics, Finance and Management. Whenever decisions in the economy are taken under uncertainty (and most decisions are taken in this way), then the concepts of random variables, their distributions and the relationship between random variables become vital to understanding the decision making process. Many modern theories in Economics and Finance build upon these ideas.

Econometrics, a subject which will be completely new to most of you, is introduced in the second part of the unit during the Spring and Summer Terms. Mathematical statistics is the foundation of Econometrics as well. Econometrics is the name given to methods developed by economists to analyse economic relationships using empirical data. If Economics has a valid claim to be a science which uses empirical observations to verify or falsify its theories and to predict future economic events, then econometrics is the means by which this is achieved. As a result, Econometrics combines ideas from both Statistics and Economics.

Intended Learning Outcomes

  • to understand the fundamentals of inferential statistics including the use of expectations, the theory of estimation and hypothesis testing
  • to understand the basics of regression analysis.

Teaching Information

27 one hour lectures, 9 one hour exercise lectures, 10 one hour tutorials.

Assessment Information

  • Formative assessment involves completing exercises for tutorial classes.
  • Summative assessment is a 3 hour unseen exam which will assess all learning outcomes.

Reading and References

  • Stock J. and Watson M. (2007) Introduction to Econometrics 3rd edition Pearson Education, New York
  • Gujarati D. and D. Porter (2010) Essentials of Econometrics (4th Edition) McGraw Hill Irwin
  • Cranshaw J. and J. Chambers (2001) A concise course in A level Statistics fourth edition Nelson Thornes
  • Mendenhall, Schaeffer and Wackerly (1990) Mathematical Statistics with applications (4th Edition) Boston: Duxbery Press

Feedback