The course of Statistical Models and Data Analysis aims to introduce the student to the discipline of statistics as a science of understanding and analyzing data. The student will learn how to effectively make use of data in the face of uncertainty: how to collect data, how to analyze data, and how to use data to make inferences and conclusions about real world phenomena.
The students need to have basic knowledge in statistics. A genuine interest in data analysis is a plus!
Data preparation; data collection and sampling; analysis of variance; multiple regression; logistic regression; factor analysis; cluster analysis; decision trees; multidimensional scaling.
The teaching activity consists of 728 hours of lectures, during which exercises are also proposed on the covered topics. Students are also assigned additional exercises to perform at home, individually or in groups, which are then corrected and discussed during the lesson hours.
Bracalente B., Cossignani M. e Mulas A . (2009), Statistica aziendale, McGraw-Hill
Zani S. e Cerioli A. (2007). Analisi dei dati e Data mining per le decisioni aziendali,
The assessment is based on an oral examination. The vote of the examination is expressed in scale from 0 to 30. To pass the exam (a vote not lower than 18/30), the student must demonstrate at least a basic knowledge of the techniques illustrated during the course.