DATA ANALYSIS

Course objectives

EDUCATIONAL OBJECTIVES The course is designed to provide students with knowledge and skills, basic and advanced, aimed at statistical data analysis. Through the use of specifically dedicated software, the application of innovative teaching strategies (learning by doing¸ problem solving, cooperative learning, etc.) and the enhancement of experiences and testimonies of professionals in the field (variously connected with institutions, associations, companies), the objective is to transmit practical knowledge and critical awareness in: selecting and querying accredited statistical sources; preparing and checking data; analyzing and synthesizing data at different levels and in a comparative key; interpreting and communicating results; and reporting. 1. Knowledge and Understanding The course aims to provide the skills necessary to be able to consciously use differentiated techniques of quantitative data analysis. Students will be guided through a shrewd descriptive statistics course that will enable them to use data from external sources (secondary data analysis); construct a data matrix; check/evaluate and analyze data; interpret results; and consciously use the most appropriate graphical-tabular representation techniques. 2. Ability to Apply Knowledge and Understanding Upon completion of the course, the student will be able to navigate the use of basic and advanced data analysis procedures; know how to appropriately choose the most relevant forms of representation; know how to make use of secondary data and metadata; and know how to interpret the results of such analyses. 3. Critical and Judgmental Skills The student will acquire the ability to develop an analysis plan and to determine the appropriateness of the data and statistical techniques applied in relation to the analysis objectives. 4. Ability to communicate what has been learned Through constant classroom exercises and the performance of group project works, the student will be able to describe, including in the context of public presentation/discussion opportunities, the rationale for the analyses performed and to communicate the results concisely and effectively, using appropriate and rigorous language. 5. Ability to continue studying independently The student will be able to apply, in an original way, descriptive statistical techniques to any thematic domain of interest. In addition, he/she will be able to independently update and expand his/her knowledge by appropriately selecting databases, official reports and sources. Finally, he/she will be able to autonomously interpret the results of research already carried out in differentiated domains, developing a critical reading and comparative skills. The skills he/she will acquire will be fully expendable in business and marketing research (corporate and brand positioning strategies; customer satisfaction; reputation analysis of companies, brands, products/services, etc.). 6. Expected Outcomes: The student will learn, from a theoretical and application perspective, the main techniques of descriptive statistics to independently and consciously perform data analysis and to appropriately and effectively communicate the results of such analysis.

Channel 1
MARIA PAOLA FAGGIANO Lecturers' profile

Program - Frequency - Exams

Course program
The course (6 cfu) aims to train students in statistical data analysis and transfer technical and practical skills in: research, selection and analysis of statistical sources; comparative reading of accredited reports on specific topics; language of variables; design, control and inspection of a dataset; preparation of an analysis plan; monovariate and bivariate analysis of primary and secondary data (including data that can be acquired from the Web and phenomena observable on social platforms); construction of empirical indices; hints at the main techniques of multivariate analysis; and reporting strategies. The intent is to build, in a participatory and operational way, a toolbox, useful for observation and interpretation of a wide range of social, economic and cultural phenomena, as well as for strategic communication of research findings. Lectures will alternate with laboratory meetings and group project works, aimed at learning the functionality of specific tools for statistical data analysis and interpretation and dissemination of results.
Prerequisites
Basic methodological skills
Books
• Fasanella, A., Mauceri, S., Nobile, S. (a cura di), (2024). Metodologia della Ricerca Sociale. Milano, Franco Angeli (capp. 10, 11, 12, 13, 14, 15, 16, 17, 18, 23, 25, 26) • Cairo, A. (2020). Come i grafici mentono. Capire meglio le informazioni visive. Milano, Raffaello Cortina • Istat, Rapporti Bes 2023. Rapporto Bes 2023: Il Benessere equo e sostenibile in Italia (report scaricabile al link https://www.istat.it/it/archivio/295254) – 3 chapters by choice Recommended readings: • Cosenza, V. (2014). Social Media ROI, Adria (RO), Apogeo Editore • Jones, B. (2020). Data analysis & visualization. Sette insidie da evitare per analizzare e rappresentare dati. Adria (RO), Apogeo Editore
Frequency
Attendance is not compulsory but strongly recommended to all students.
Exam mode
For attending students: - In progress evaluation of the skills, on the basis of individual and group exercises. - Project Works on specific research topics, within which the design aspects and argumentative skills, the operations of analysis and synthesis carried out, the presentation and interpretation of the results obtained, and the ways of communicating the results/public discussion of the work done play a central role. For non-attending students: - Oral examination
Lesson mode
Lectures alternated with individual and group exercises
MARIA PAOLA FAGGIANO Lecturers' profile

Program - Frequency - Exams

Course program
The course (6 cfu) aims to train students in statistical data analysis and transfer technical and practical skills in: research, selection and analysis of statistical sources; comparative reading of accredited reports on specific topics; language of variables; design, control and inspection of a dataset; preparation of an analysis plan; monovariate and bivariate analysis of primary and secondary data (including data that can be acquired from the Web and phenomena observable on social platforms); construction of empirical indices; hints at the main techniques of multivariate analysis; and reporting strategies. The intent is to build, in a participatory and operational way, a toolbox, useful for observation and interpretation of a wide range of social, economic and cultural phenomena, as well as for strategic communication of research findings. Lectures will alternate with laboratory meetings and group project works, aimed at learning the functionality of specific tools for statistical data analysis and interpretation and dissemination of results.
Prerequisites
Basic methodological skills
Books
• Fasanella, A., Mauceri, S., Nobile, S. (a cura di), (2024). Metodologia della Ricerca Sociale. Milano, Franco Angeli (capp. 10, 11, 12, 13, 14, 15, 16, 17, 18, 23, 25, 26) • Cairo, A. (2020). Come i grafici mentono. Capire meglio le informazioni visive. Milano, Raffaello Cortina • Istat, Rapporti Bes 2023. Rapporto Bes 2023: Il Benessere equo e sostenibile in Italia (report scaricabile al link https://www.istat.it/it/archivio/295254) – 3 chapters by choice Recommended readings: • Cosenza, V. (2014). Social Media ROI, Adria (RO), Apogeo Editore • Jones, B. (2020). Data analysis & visualization. Sette insidie da evitare per analizzare e rappresentare dati. Adria (RO), Apogeo Editore
Frequency
Attendance is not compulsory but strongly recommended to all students.
Exam mode
For attending students: - In progress evaluation of the skills, on the basis of individual and group exercises. - Project Works on specific research topics, within which the design aspects and argumentative skills, the operations of analysis and synthesis carried out, the presentation and interpretation of the results obtained, and the ways of communicating the results/public discussion of the work done play a central role. For non-attending students: - Oral examination
Lesson mode
Lectures alternated with individual and group exercises
  • Lesson code10612042
  • Academic year2025/2026
  • CourseOrganization and Marketing for Corporate Communication
  • CurriculumComunicazione integrata e data analysis
  • Year2nd year
  • Semester1st semester
  • SSDSPS/07
  • CFU6
  • Subject areaAttività formative affini o integrative