This is one of the two modules of the “Advanced data analysis and statistics” course. This module grants 3 CFUs and its aim is to provide the mathematical knowledge and methodological basis that will be used in subsequent courses. The course is based on a theoretical as well as applied approach.

Students are invited to consult the syllabus of the entire course for details regarding learning- and skill-related objectives.

Learning Objectives:
Knowledge and Understanding: students will become familiar with linear algebra (vectors, matrices, eigenvalues, and quadratic forms) and differential calculus of several variables (partial derivatives, optimization, and Lagrange multipliers).

Applying Knowledge and Understanding: students will be able to apply mathematical techniques, including matrix algebra, systems of linear equations, and constrained optimization, to solve problems in data analysis.

Making Judgements: students will develop the ability to critically assess the suitability of mathematical methods for real-life problems, evaluating the validity of solutions and their implications in analytical contexts.

Communication Skills: students will be able to clearly present mathematical solutions and their interpretations in written exams, using precise mathematical language and formal reasoning.

Learning Skills: students will gain the skills to independently study advanced mathematical topics relevant to data analysis, enabling them to succeed in subsequent courses and pursue further academic or professional development.