Statistics

The main objective of the course is to ensure that students acquire an adequate knowledge and degree of understanding of the appropriate tools to synthetically describe one or more characters of interest that are found in the most various fields (political, administrative, sociological, historical, legal, economic, etc.). This description can be made by aggregating the data observed in tables, giving an adequate graphical representation, constructing appropriate position and variability indices, identifying the most appropriate measures that highlight the relationships. The statistical description must be accompanied by statistical induction, when the survey is not total but partial; in this case, the knowledge of the aforesaid characters is not in "certain" terms but only "probable" and has the purpose of providing indications on the entire population of reference. The basic topics of Probability and Statistical inference are therefore provided. Knowledge and understanding of these tools require a strong application capacity. Students will have to develop a marked independence of judgment, in order to be able to adequately choose the most suitable techniques for solving the proposed problems, and they will have to demonstrate that they also possess communication skills, essential to be able to explain the methodologies and logical paths used in solving the questions. Finally, they must acquire a more and more refined learning ability, which will allow them to face new situations with a high degree of autonomy.

At the end of this course, the student is expected to know and use the main statistical tools necessary for the analysis of phenomena in different fields (social, economic, etc) and in their various manifestations. The student will be able to organize the observed data of one or more phenomena of interest in a frequency or contingency table, to synthesize their main features and relationships through appropriate univariate or bivariate indices, and to infer more general results about the population from the observed sample data.