Quantitative Marketing Research and Statistical Data Analysis
Marketing professionals rely on information gathered through marketing research to determine the course of action of a marketing plan. Leveraging upon research to know more about customers, consumers, and citizens is crucial for effective marketing decisions. In the first part of this course (“Quantitative Marketing Research”), students will learn how to be smart producers and consumers of information, when it comes to marketing research. They will also learn to be more effective marketing decision makers. The course is organized interactively, with lectures, in-class exercises, group and individual assignments.
In the second part (“Statistical Data Analysis”), the course will address market research data interpretation based-upon quantitative data and techniques. The course will familiarise participants with statistical data analysis - the art of examining, summarising and drawing conclusions from data. This includes the organisation of a coherent database and its use to produce statistical summaries and inference. Statistical software is essential in this respect. While building on students’ prior knowledge of introductory level statistics, such as frequency, distribution and correlation, the course will introduce new topics, including hypothesis testing on means, percentage and regression, multiple regression, logistic regression, factor analysis and cluster analysis.
This course will enable students to:
• manage sampling methods for quantitative marketing
• familiarize with key quantitative marketing research methods and associate them with marketing problems they are suited to answer
• become knowledgeable about the most important quantitative marketing research tools (survey and experiment)
• understand a research brief and a research report suitable to support strategic marketing decisions
• understand the logic of the quantitative approach in data analysis
• familiarise with main concepts in probability and statistics
• get introduced to inferential statistical methods
• have hands-on experience on statistical software
• Traditional lectures
• In-class exercises and assignments
• Laboratory guided sessions
Although not compulsory, due to the nature of the topics treated and the need of assistance during the practical laboratories, attendance is highly recommended for all students.
• 20% individual assignments
• 30% group assignments
• 50% final exam in a form of a written online test in English*
*To answer the final test’s questions, it will be necessary to perform some calculations with the dedicated software introduced in the course.