The course aims at providing students with an overview of the main tools for market analysis, demand forecasting and statistical models construction. The application context will cover concrete cases of market analysis to support business decisions in the passenger transport sector. The course will be carried out entirely in the computer lab to provide students with specific skills in the management and analysis of datasets. The exercises will be carried out using the most common software for data management and statistical analysis (Excel, R and STATA).
The course aims to provide students with an overview of the main tools for market analysis, demand forecasting and the construction of statistical models. The application context will cover real cases of analysis in support of business decisions in the field of maritime passenger transport. The course will be carried out entirely in the computer lab to provide students with specific skills in the management and analysis of datasets, including large ones. The exercises will be carried out using the most common software for data management and statistical analysis (Excel, R and STATA).
At the end of the course the student will be able to:
planning and analysing the results of a sample survey aimed at measuring the satisfaction of a transport service; managing and analysing company data for market segmentation; build statistical models. The course also aims to provide students with the basic knowledge necessary to make them autonomous in the study and subsequent use of the most advanced statistical methodologies.
Lectures, statistical lab in computer room, case studies analysis, independent homework and group work.
The detailed course syllabus covers the following topics.
Transportation Statistics Sources and the Principles of Economic and Business Research
Official statistics, primary data, and secondary data The phases of research on observational data Tools for representing spatial data The sample Survey for measuring passenger satisfaction
Recalls on the principles of point and interval estimation The questionnaire as a tool for measuring economic phenomena Techniques for constructing rating scales Probabilistic and non-probabilistic sampling techniques Population stratification Sampling and non-sampling errors Evaluation of marketing policies through the construction of interpretative models
Analysis of variance and its non-parametric alternatives Multiple linear regression: regression diagnostics and problems related to the violation of OLS model assumptions with hints on generalized linear models Market segmentation: methods of multivariate statistical analysis for customer segmentation aimed at profiling passengers and cruise passengers.
Principal component analysis and factor analysis Cluster analysis for market segmentation Business Intelligence Statistical tools for monitoring of customer base and for the construction of growth scenarios
The estimation of transportation demand through the classical approach to time series analysis
Methods of decomposition of time series into its components Moving average and exponential smoothing methods
Notes from the lessons and materials made available on Aulaweb
Biggeri L., Bini M., Coli A., Grassini L., Maltagliati M. (2012) Statistica per le decisioni aziendali, Pearson.
Washington S.P., Karlaftis M.G., Mannering F.L. (2011) Statistical and econometric methods for transportation data analysis. Chapman&Hall.
Mazzocchi M., Statistics for marketing and consumer research, Sage.
Ricevimento: Always by appointment, to be agreed by direct message via MS Teams platform.
LUCA PERSICO (President)
ENRICO DI BELLA
CORRADO LAGAZIO
First semester
The examination will take place in oral form through the discussion of a written work.
The verification of the acquired competences will take place both in itinere through the evaluation of individual tests and group works and at the end of the teaching period through a written test.
