MAN-20145 - Module Specification
Keele Business School
Faculty of Humanities and Social Sciences

Programme/Approved Electives for 2025/26

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2025/26

There is a wide range of analytic techniques that organisations can use to address operational and strategic challenges. In this module we will study how organisations can make choices about the data and techniques that they use in specific cases. We will use the CRISP-DM model as a way to understand the process. We will then study common analytic models such as clustering, decision trees, regression and neural networks identifying their strengths, limitations and potential application.

The aims of this module are to equip students with an awareness of the range of analytic techniques available to organisations, the uses and the principles that underpin their implementation. Whilst the coding required to implement the various models is beyond the scope of the module students will be able to explain the way models work, their use and the situations where each may be used to inform organisation operations or decision making. The CRISP-DM model will be used to develop students' understanding of the application of analytics in organisations.

Intended Learning Outcomes

Explain and evaluate a broad range of analytic and predictive models and suggest where they may be used: 1,2
Analyse an organisational challenge and suggest analytic techniques that may be deployed to address it: 1,2
Explain and apply the CRISP-DM framework to the development of analytics based solutions to organisational challenges: 2

Study hours

8x2 hour lecture sessions
8x1 hour seminars
126 Independent study. 30 hours will be used for the group assignment and 80 for the individual task. The remaining hours will be used preparing for seminars and working on self-learning packages eg. from LinkedIn Learning

School Rules

None

Description of Module Assessment