Module Information

Module Identifier
Module Title
Academic Year
Semester 2
Mutually Exclusive

Course Delivery

Delivery Type Delivery length / details
Lecture 18 Hours. (18 x 1 hour lectures)
Seminars / Tutorials 6 Hours. (6 x 1 hour tutorials)
Practical 2 Hours. (2 x 1 hour computer practicals)


Assessment Type Assessment length / details Proportion
Semester Assessment continuous assessment  20%
Semester Exam 2 Hours   (written examination)  80%
Supplementary Exam 2 Hours   Repeat Failed Elements or equivalent  Written exam  100%

Learning Outcomes

On completion of this 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;

* Calculate and interpret expectations;

* Solve simple linear programming problems;

* Use and interpret the output from statistical software.


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 : scatterplots; the idea of a line of best fit; importance of the mean point; least squares regression; the existence of two regression lines for bivariate data; 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; binomial probabilities.
5. LINEAR PROGRAMMING: equations of straight lines; formulating simple linear programming problems; feasible regions; the objective line; deducing the optimum.

The computer package MINITAB: introduction, producing and interpreting diagrams and tables, producing and interpreting summary measures; regression and correlation.


To introduce students to quantitative methods and to appreciate their importance in business.

Brief description

This module introduces statistical methods and the application of formal decision models in a business context, together with the use of statistical computer software. The software package MINITAB is used in practical classes.

Reading List

Supplementary Text
Swift, Louise. (2001.) Quantitative methods for business, management and finance /Louise Swift. Palgrave Primo search
Consult For Futher Information
Croft, Anthony (1997.) Foundation maths /Anthony Croft, Robert Davison. Addison Wesley Primo search Curwin, J, and Slater, R, (1996) Quantitative Methods for Business Decisions 5/e International Thomson Business Press Primo search Curwin, Jon (2000.) Improve your maths :a refresher course /Jon Curwin and Roger Slater. Business Press Primo search


This module is at CQFW Level 4