The course intends to approach students to data analysis, furnishing them the essential instruments to study and describe all phenomena, by using graphical representations and summary measures. A brief monographic part of the course intends to furnish some fundamental notions about probability and inferential statistic. For some proposed arguments it will be show applications on real data by using the software Excel.

Knowledge and understanding: The student - by participating in the lectures and practical activities of the course - will acquire the basic statistical knowledge necessary to analyse legal, economic, and business data. Specifically, topics related to descriptive statistics, probability, and statistical inference will be addressed. The presence of exercises during the course will allow to give an empirical vision to the statistical methodologies. Applying knowledge and understanding: The student - by acquiring appropriate tools and methods - will be able to develop critical skills in empirical analysis, through the application of statistical techniques to the study of real phenomena. The carrying out of homework will allow to verify the skills acquired by the students. Making judgements: The student, through the use of the methodologies acquired during the course, will be able to collect, process, analyse, and interpret statistical data, acquiring the ability to independently evaluate such data also with reference to concrete situations. Communication skills: The student will be able to communicate to other people, with appropriate terminology, information and evaluations related to statistical analyses, including those of legal typology. Learning skills: The knowledge acquired during the course will allow the student to autonomously understand and interpret statistical analyses. The student will develop a solid knowledge of the fundamental aspects of basic statistics that will allow him to continue to deepen the topics addressed independently, acquiring a working method useful for continuous training in his own working context

Introduction to statistical methodology. Nature and measure of statistical features. Frequency distributions. Graphical representations. Distribution summary: position measures, variability and shape. Contingency tables and indipendency between characters. Correlation. Basic concepts about probability. Indipendency. Random variables. Essentials on sampling and sampling distributions. Essentials on inferential statistics, with particular reference to estimation problems on a population.

Handbook: A. Agresti, C. Franklin (2016) Statistica – l’arte e la scienza d’imparare dai dati, Pearson Italia, Milano (a cura di G. Espa, R. Micciolo, D. Giuliani, M.M. Dickson). G. Espa, R. Micciolo (2008) Problemi ed Esperimenti di Statistica con R, Apogeo, Milano. G. Espa, R. Micciolo (2012) Analisi esplorativa dei dati con R, Apogeo, Milano Suggested and supplementary lectures: M. Piattelli Palmarini (1995) L’illusione di sapere, Oscar Mondadori, Saggi, Milano. G. Gigerenzer (2003) Quando i numeri ingannano, Raffaello Cortina Editore, Milano. T. Boeri (2005) Preface of book by Levitt S.D., Dubner S.J. (2005) Freakonomics – il calcolo dell’incalcolabile, Sperling & Kupfer Editori, Milano, pp. IX–XIV. N. Silver (2013) Il Segnale e il Rumore. Arte e Scienza della Previsione, Fandango Libri, Milano.

Lectures with the assistance of computer presentations used during the lessons. All presentations will be available for students since the first lessons on web page of the course. On the same web page, it will be available all the course materials relative to exercise lessons: exercises text and real data-sets for case study analysis, with the assistance of the software Excel.

The verification of the learning outcomes will be carried out through a written exam. This will cover the whole program of the course, both in its theoretical and practical aspects. The written test will be composed of multiple-choice questions and open questions. The grade is expressed in thirtieths. The final evaluation is made by adding the scores obtained, on the basis of the answers given to the questions of the test. The failure to achieve at least the score of 18/30 will result in failure to pass the exam. Correct answers to all multiple-choice questions and an excellent level of preparation in all open questions will result in a score of 30/30 cum laude.

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