Module Information

Module Identifier
Module Title
Statistics for Economists
Academic Year
Semester 2
Also available in
Other Staff

Course Delivery

Delivery Type Delivery length / details
Lecture 22 x 1 Hour Lectures
Practical 2 x 1 Hour Practicals
Tutorial 2 x 1 Hour Tutorials


Assessment Type Assessment length / details Proportion
Semester Assessment continuous assessment  20%
Semester Exam 1.5 Hours   (Written Examination)  80%
Supplementary Exam 2 Hours   (Written Examination)  100%

Learning Outcomes

On completion of the module, a student should be able to:

* Summarise and present a data set;

* Calculate various summary measures for grouped and ungrouped data;

* Construct and interpret statistical diagrams;

* Fit a straight line to suitable data;

* Calculate and interpret correlations;

* Describe and illustrate basic probability concepts;

* Use statistical tables;

* Carry out and interpret the results of basic statistical tests;

* Use and interpret the output from statistical software.

Brief description

This module introduces statistical methods and their application, basic ideas from probability, together with the use of statistical tools in Excel


To introduce students to statistical methods and to appreciate their importance in Economics.


1. STATISTICAL DIAGRAMS: pie charts; simple multiple and stacked barcharts; histograms; cumulative polygons; stem and leaf diagrams
2. SUMMARY MEASURES: minimum, maximum, median, quartiles, percentiles; five number summaries and box-and-whisker plots; mean and mode; variance and standard deviation; calculations from grouped data.
3. SCATTERPLOTS, REGRESSION AND CORRELATION. Contingency tables, scatterplots; the idea of a line of best fit; importance of the mean point; least squares regression; correlation and its measurement; the (product moment) correlation coefficient; Spearman'r rank correlation.
4. PROBABILITY: Definition and properties; unions and intersections; mutually exclusive events; the addition law; independent events; the multiplication law; equally likely outcomes; conditional probability; Bayes's theorem; the Central Limit Theorem; the Binomial distribution; the Normal distribution.
5. STATISTICAL INFERENCE: basic ideas; informal inference based on 'rwo standard deviations?; formal p-values; goodness of fit; the idea of a confidence interval.
6. COMPUTER-AIDED STATISTICS. With the aid of Excel: produce and interpret diagrams, tables and summary measures; compute correlation and regression; motivate probability distributions and the Central Limit Theorem.


This module is at CQFW Level 4