Learning objectives
The purpose is to deal in a quantitative way the relevant information for
the firm using advanced computer programming. The data can come from different sources (internal or sample
surveys or web sites) . The final goal is to provide a rational support for decision
making using computer programming.
Prerequisites
Basic knowledge of mathematics and statistics
Course unit content
Multivariate data analysis: data warehouse and data mining.
Exploratory data analysis: missing values and outliers
Introduction to MATLAB and to computer programming.
Dimension reduction: principal component analysis. Applications to
marketing problems.
Statistical methods for market segmentation: cluster analysis. Sentiment analysis. Introduction to machine learning.
Full programme
Multivariate data analysis: data warehouse and data mining.
Exploratory data analysis: missing values and outliers
Introduction to MATLAB and to computer programming.
Dimension reduction: principal component analysis. Applications to
marketing problems.
Statistical methods for market segmentation: cluster analysis. Introduction to machine learning and sentiment analysis.
Bibliography
Material downloadable from web site http://www.riani.it/SDE
Teaching methods
Frontal lessons with PC and practical lesson using Matlab.
Assessment methods and criteria
Exam using the computer
Other information
Additional information can be found from the web site http://www.riani.it
2030 agenda goals for sustainable development
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