Advanced Data Analysis
Learning outcomes of the course unit
The course gives advanced knowledge on statistical techniques for Marketing and Management applications.
The aim of the course is
1. To strenghten the methodological and applied expertise on key methods of model building, classification and prediction.
2. To introduce a few specialized techniques.
3. Using real case studies and emphasizing the learning-by-doing approach, to illustrate the application and the interpretation of these methods.
Computational aspects of the methods are addressed through the use of MS Excel and IBM SPSS.
The course requires knowledge of the contents of the course on "Statistical Methods for Management", and attendance to the related course on "Data Mining for Marketing"
Course contents summary
The course provides more advanced knowledge on statistical techniqes for data analysis in Marketing and Management. Specifically, the course will address:
a) association measures among purchased items for Market Basket Analysis;
b) advanced models for the analysis of consumer behaviour;
c) advanced techniques for consumer segmentation.
The course will cover both the statistical theory behind these techniques and their application potential. Emphasis will also be placed on computational aspects, through the use of MS Excel and IBM SPSS.
Lectures; seminars of external experts; practical work.
Details on the timetable will be provided to the class and made available through the web site:
Assessment methods and criteria
Oral exam and discussion on the results of real case studies.
Knowledge and understanding will be assessed by methodological questions, which will assign 12 grade points in total. The ability of applying knowledge and understanding will be assessed through the discussion of the results of real case studies, which will assign 12 grade points in total. Learning skills will be assessed by questions on the conclusions to be drawn from an analysis, which will assign 6 grade points in total.
The case studies to be discussed will be provided to the class and made available through the web site: