Business Management

General Objectives The course provides students with the necessary knowledge to understand the main statistical methodologies useful to formulate, estimate and validate linear regression models and for discrete data. Particular emphasis will be given to applications in the business, socio-economic and financial fields, aimed at the analysis of specific business management problems and the evaluation and control of business processes. Through case studies, classroom exercises and group work, students will learn how to use the statistical software R, not only as a working tool, but also as a tool of deepening the theoretical models and their applicability to real data. Furthermore, starting from the analysis of real data, students will acquire the ability to discriminate between alternative statistical procedures, evaluating their advantages and disadvantages, as well as to critically read and understand scientific articles that make use of procedures that are not illustrated in the course. Specific Objectives Knowledge and understanding: The course provides students with the knowledge to specify and estimate a regression model and to interpret the results of an estimation procedure. Applying knowledge and understanding: Through classroom exercises, case studies and group work, the course supports students in carrying out an empirical analysis using statistical software. At the end of the course, students will be able to study the relationships between two or more variables (qualitative and/or quantitative), explain the variability observed in the data and critically analyse the results obtained. Making judgements: The content and methods of the course enable students who successfully pass the examination to acquire a sensitivity to empirical data analysis; using the methodological tools introduced in the course, students will be able to discriminate between different statistical procedures and to critically evaluate the results. Comunicaton skills: The course also contributes to strengthen oral exposition and synthesis skills, as attending students are invited to carry out group work, the results of which are to be summarised in a short report and publicly presented to all other students. Learning skills: The course guarantees the acquisition of a high level of autonomy in the management of study and learning. This is made possible through classroom activities which, starting from real problems, encourage students to evaluate the advantages and disadvantages of the procedures adopted, providing them with the appropriate approach for the autonomous understanding of alternative statistical models, not introduced in the course, and their evaluation in terms of advantages and limitations.