Statistics for Economics - EC309

Location Term Level Credits (ECTS) Current Convenor 2018-19
Canterbury
(version 2)
Spring
View Timetable
4 15 (7.5) PROF AA Carruth

Pre-requisites

None

Restrictions

Not available to students taking CB314 Quantitative Models and Methods for Accounting and Finance. Not available as a wild module.

2018-19

Overview

This module introduces students to the basic concepts of probability and statistics, with applications to a variety of topics illustrated with real data. The techniques that are discussed can be used in their own right to solve simple problems, but also serve as an important foundation for later, more advanced, modules. Importantly, the module serves as a prerequisite for Stage 2 econometric modules EC580 and EC581.
The module commences with an overview of descriptive statistics. It then considers the key ideas in probability theory before moving on to statistical inference - the science of drawing conclusions from data. The main topics covered in the module include:

  • Graphical and numerical analyses of data
  • The principles of probability
  • Probability Density Functions
  • Sampling and its use in inference
  • Regression and correlation
  • Details

    This module appears in:


    Contact hours

    22 lectures
    10 seminars
    10 drop-ins

    Availability

    This module is compulsory for all students studying single and joint honours degrees in Economics.
    This module is not available to students across other degree programmes in the University.

    Method of assessment

    In Course Test (90 minutes) (20%)
    Examination (2 hours) (80%)

    Indicative reading

    M Barrow, Statistics for Economics, Accounting and Business Studies, (7th ed), Longman
    T H and R J Wonnacott, Introductory Statistics for Business and Economics, Wiley (any edition)

    See the library reading list for this module (Canterbury)

    See the library reading list for this module (Medway)

    Learning outcomes

    By the end of the module, you will be able to:
    * organise, describe and summarise data.
    * understand the principles of probability.
    * understand the principles underlying sampling theory.
    * apply hypothesis testing and interval estimation to sample data.
    * use regression analysis to consider relationships between two variables.

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