Module BUSI3511: Quantitative Analysis for Marketing Decision Making

Department: Management and Marketing

BUSI3511: Quantitative Analysis for Marketing Decision Making

Tied To

• N509: Marketing and Management
• N510: Marketing and Management with Placement Year
• N511: Marketing and Management with Study Abroad

Pre-requisites

Corequisites

Excluded Combinations

Aims

• To provide students with an understanding of quantitative analysis techniques and their application in marketing decision-making.
• To enhance student ability to interpret quantitative data effectively.
• To develop skills in using quantitative data to inform and support marketing strategies.

Content

• Revision of statistics - descriptive. Measures of central tendency, measures of dispersion, cross-tabulations.
• Revision of statistics – inferential. Regression, correlation, contrast codes, multiple regression.
• Psychometrics – Even vs. odd numbered scales, attention checks, reverse scales, questionnaire design.
• Costs – fixed, variable, opportunity, sunk, relevant. Break-even analysis and budgeting.
• Time – net present value, future value, expected value, customer lifetime value.
• Probability – independent, conditional, repeated events.
• Optimisation with solver – Linear programming, Binary programming, Programming for break-even and profit.
• Operations research tools – critical path method, queuing theory, sales assignment.
• Distance measures – Cluster analysis, multi-dimensional scaling, conjoint analysis.

Learning Outcomes

• Knowledge of key quantitative analysis techniques.
• Understanding on how various quantitative analysis techniques can be applied to support marketing decision making.

• Ability to apply quantitative methods to analyse marketing data.
• Ability to interpret and present quantitative data in a clear and meaningful way.
• Ability to make informed marketing decision based on data analysis.

• Communication, both written and verbally.
• Problem-solving.
• Critical thinking.
• Numeracy.
• Computer literacy: SPSS and other statistics software.

Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module

• Teaching is via lectures and lab sessions. Learning takes place through attendance at lectures, preparation for and participation in lab sessions, and private study.
• Formative assessment is by means of a range of in-class activities.
• Summative assessment is one individual report on proposing solutions based on data analysis for a specific business scenario.

Teaching Methods and Learning Hours

Summative Assessment

Formative Assessment

Quizzes delivered via Learn Ultra at the end of each seminar session