Learning objectives

The course is included in the learning area New technologies and data management. It aims to provide students with an understanding of statistical concepts and the ability to conduct statistical analyses useful in the professional contexts. Topics include descriptive statistics, inferential statistics and correlational models, and open source statistical packages will be used. Basic skills will be given in designing, executing, analysing, interpreting, and reporting applied research.
By the end of the course students will be able to describe and use some techniques of data collection and data analysis, and report and discuss the results.
At the end of the course, the student will also have acquired the ability to face and solve practical problems typical of the professional context in which he/she will operate, thus orienting his/her competence to the goal of contractual compliance and to the prevention of the judicial conflict. He/she will be able to verify the practical and applicative consequences of the theoretical and regulatory framework and to set, in written and oral form (and also through group working, written exercises and the method of Problem Based Solving - PBS), the solution of concrete issues, using the appropriate and specific disciplinary vocabulary, adopting the correct lines of reasoning and argumentation, and formulating autonomous judgments. The teaching method used is functional to the continuous learning and updating of acquired knowledge.

Prerequisites and basic notions

The knowledge acquired during the first year of the course is a prerequisite.

Program

Topics to be covered include learning quantitative and qualitative data collection techniques, analyzing the quality of collected data, using data analysis techniques including analysis of variance, multiple regressions, and the drafting of a summary report of the results. Students will use real data and law-related examples to illustrate the concepts and tools being taught. In particular, the knowledge and skills are achieved through the following training activities: 1. From theory to practice: reflections on starting a data analysis process. 2. From field survey to analysis phase: construction and organization of a database or interpretation of an existing database 3. Introduction to the use of the open-source statistical package Jamovi: Jamovi and database management. 4. Analysis of the quality of the collected data. 5. To measure in particular the causal link between the observed variables: simple and multiple regression. 6. Use of more complex models: mediation and moderation 7. Preparation of a report summarizing the results
No textbook is provided, but slides and other digital materials will be made available to students

Bibliography

Didactic methods

The course program will be taught through lectures, exercises, and group work. During the exercises, the techniques learned during the lessons will be tested using software such as Excel and Jamovi. The Moodle platform will also be used to support the course activities. The program is the same for both attending and non-attending students. Recordings of the lectures will be made available to students with disabilities or learning disabilities upon request prior to the start of the course.

Learning assessment procedures

The exam lasts one hour. It is a written exam and consists of a series of exercises designed to test the student's knowledge of the topics covered in the course, using Excel and Jamovi. Erasmus students are encouraged to contact the instructor to arrange the exam. Please note that Erasmus students may take the exam in English during an oral interview, following the same content and procedures as those described for other students.

Evaluation criteria

The aim of the test is to ascertain the achievement of the expected teaching outcomes, in terms of theoretical and applied knowledge and understanding.

Criteria for the composition of the final grade

The final grade is the sum of the scores obtained from solving the proposed exercises. For example, there will be 8 questions, each of which can be scored up to 4 points. The score will be awarded not only based on the solution to the question but also on the interpretation of the results of the analysis performed.

Exam language

italiano