Knowledge and understanding

The course focuses on the formation of data-driven opinions and decisions. In particular, it examines the epistemological processes through which knowledge is generated from data. To this end, the course first emphasizes statistical literacy in a context of rapidly increasing information production, where communicative overload requires individuals to navigate the "asymmetry of information" and distinguish between data that are scientifically authoritative and data that are not.
The course familiarizes students with ISTAT, the Italian National Institute of Statistics, as the official statistical authority and a public good serving citizens. It then broadens its scope to include other official and alternative data sources, as well as Big Data. The development and use of metadata become crucial tools for interpreting data, together with systems for assessing and validating data quality. These aspects are examined within the broader framework of supranational statistical systems such as Eurostat, the OECD, and the World Health Organization (WHO).
From the perspective of statistical methodology, the course starts from the main constructs used in the study of behavior, which represent an interdisciplinary thread running through the degree program. Beginning with the conceptualization of these constructs, the course illustrates how they are operationalized for empirical research through the construction of statistical variables and related measures.
The course then introduces data analysis within the two main branches of statistics: descriptive statistics and statistical inference. Particular emphasis is placed on the dual role of descriptive statistics, both in its own right as a means of understanding a population or group, and as an essential prerequisite for the correct application of inferential methods.

Applying knowledge and understanding

Concepts, definitions, and disciplinary tools will be systematically presented from an interdisciplinary perspective, fostering the ability to integrate the statistical procedures learned in the course with information sources of different kinds.
The competencies developed in the course have a dual applied focus.
First, becoming familiar with data collection processes and the associated measurement systems used in official statistical production enables students to interpret data correctly and avoid misleading approaches. This is achieved through the ability to identify and investigate the key contextual and methodological elements that have generated the data, as well as through the practice of accurate data reading, appropriate data processing, and critical interpretation of results.
Second, through the methodological foundations of the discipline, students will learn how to organize collected data based on their understanding of measurement scales. The practical application of these scales will enable them to derive the appropriate descriptive measures for both univariate and bivariate analysis. Descriptive summaries will also serve as a guide to the inferential possibilities available.
Finally, the use of open-source statistical software will strengthen students' proficiency in applying statistical methods and in understanding the meaning and interpretation of different statistical measures.

Making judgements

The ability to exercise independent judgment and critical thinking in understanding the vast amount of data that permeates both scientific literature and information more generally is an essential driver for navigating contemporary communication, which relies on multiple forms of language.
Developing sensitivity to the processes through which data are generated enables students to interpret data correctly, place them within their original contexts, and understand the conditions and limitations of the measurement procedures that define their content. During the course, students will engage in the direct examination of quantitative information drawn from different sources, exercising critical thinking to avoid superficial interpretations and refining strategies and approaches aimed at preventing oversimplification.
This perspective will then be extended to alternative data sources and, more broadly, to public communication, with particular attention to decoding the strategies used in the presentation of information.
Independent judgment and critical thinking will be explicitly fostered through data processing activities, the construction of indices and indicators, and the selection of the most appropriate statistical measures according to the characteristics of the phenomenon under investigation.
Statistical modeling will be introduced through bivariate analysis across different measurement scales, with attention to identifying misleading interpretations such as spurious correlation and Simpson’s paradox.
These competencies will be developed both through classroom and computer-lab activities and through the assessment methods adopted in the course.

Communication skills

Statistical literacy is a crucial component of the skill set of graduates in Communication Sciences, both for a full understanding of the scientific literature—which relies heavily on empirical validation—and for the ability to communicate complex content through appropriately diverse and integrated forms of expression.
Students will develop the ability to present summarized data in both numerical and graphical forms, while simultaneously explaining their empirical meaning, definitions, and metadata, thereby clarifying their scope and preventing naïve interpretative distortions.
They will also become proficient in communicating statistical phenomena through graphs, tables, and verbal descriptions, adapting the format to the intended purpose and audience.
Classroom activities and individual exercises, which will be discussed and reviewed during dedicated sessions, will help students consolidate these communication skills. These competencies will also form part of the assessment process in the course examinations.

Learning skills

The teaching structure of the course is aligned with the overall perspective of the degree program, which seeks to promote a style of learning that integrates different disciplines within a multidimensional educational framework. This approach is aimed at enhancing the knowledge and skills needed to address the complexity of contemporary communication.
The continuation of academic training is oriented toward information systems for communication and information management, as well as evidence-based humanities disciplines.
The development of students' autonomy and the consolidation of their learning abilities will be supported through both individual and group activities and will subsequently be assessed through the final examinations