03383 - Social Statistics

Learning outcomes

Upon completion of the course, students will: - understand and be able to use the basic tools of quantitative analysis and verification of results in social research; - be able to correctly interpret and critically evaluate the results of investigations that involve the use of statistical data analysis techniques.

Course contents

One of the tasks of social workers is to contribute—along with other professionals—to the formulation of local plans, with the aim of understanding the users in their area of responsibility, mapping their needs, and planning interventions and solutions. Therefore, this professional must be familiar with statistical social studies, understand how they work, and know the correct application of various statistical techniques.

To facilitate learning, lessons are organized into logical blocks:

1) basic concepts: types of properties and types of variables; operational definition; hypotheses.

2) statistical data processing (univariate and bivariate analysis); graphical representations.

3) second-level analysis: statistical sources; indicators; interpretation of statistical data.

Readings/Bibliography

White P. (2026), Statistica semplice, Egea, Milano.

Marradi A. (2007), Metodologia delle scienze sociali, il Mulino, Bologna. Capitolo 8 “Indicatori, validità e costruzione di indici”.

Niero M. (2004), Metodi e tecniche di ricerca per il servizio sociale, Carocci, Roma. Capitolo 2 “L’analisi d’ambiente” (e Appendici); Capitolo 6 “La misura degli atteggiamenti e della qualità della vita”.

Teaching methods

The course will be taught through lectures.

In each session, the instructor will cover a topic in its essential components, using PowerPoint presentations.

The PowerPoint presentations used will be available on the Degree Program website, next to the teaching materials, one week before the lecture. They are clearly identified by the topic they refer to and the date of the lecture in which they will be covered.

It is recommended to use the material during the lecture as a listening guide. Please note that the slides do not replace the study of the exam texts, but rather serve as a support for understanding them.

Assessment methods

The exam consists of a written test on basic concepts and statistical data processing, and an oral exam on second-level analysis (indicators and rating scales).

The written test will be administered in person via EOL and will consist of multiple-choice questions.

The score, from 0 to 30, will be the sum of the points awarded for each correct answer. Incorrect answers will not be awarded points (nor will they be deducted from the total score). To pass the written test, students must achieve a score of 18/30 or higher.

A successful written test remains valid until the remedial session scheduled for September 2027. Students who will not sustain (or fail) the oral exam will be required to retake the entire exam after that date.

For the final oral exam, the evaluation criteria focus on three areas:

1. ability to understand the topic and develop its essential components (grade range 18-22);

2. Accuracy in discussing the individual components of the topic (grade range 23-26);

3. Mastery of the presentation style (grade range 27-30).

To obtain a passing grade, the exact execution of point (1) is required.

The exam syllabus is the same for both attending and non-attending students; the only difference is the assessment method.

ATTENDING STUDENTS are those who take the written exam during the lecture period.

NON-ATTENDING STUDENTS, i.e., those who have not taken or passed the partial exam during the lecture period, will take the exam on the entire syllabus during the summer session and the remedial session (September), taking the written exam first and then the oral exam.

AI can be a useful tool to support individual study with in-depth analysis, summaries, and self-assessment paths. Regarding learning assessment, the use of AI is prohibited during the in-person exam. Any use constitutes a violation of academic integrity.

Teaching tools

PowerPoint slides.

Office hours

See the website of Francesca Cremonini