Lecture: Introduction to data analysis: mathematical background and computational tools in industrial engineering

Ing. Riccardo Rossi


This course provides an overview of the fundamental concepts and computational tools for analysing and interpreting experimental data. Even if the emphasis is on practical applications, the underlying theory is also covered, with particular attention to the basic statistical concepts underlying the most widely spread software packages. The course covers both classification and regression and includes estimation, confidence intervals and hypothesis testing, with an introduction to robust statistics. Particular attention is devoted to modern machine learning tools, from neural Networks to Support Vector Machines, and their role in exploratory methods for knowledge discovery. Since the aim is the introduction to techniques for scientific applications, model selection methods, causality determination and time series analysis are integral part of the programme.