Applied Social Research
A.Y. 2025/2026
Learning objectives
Il corso ha l'obiettivo di fornire le competenze essenziali per progettare e condurre ricerche sociali in modo efficace, con particolare attenzione all'approccio quantitativo. Gli studenti acquisiranno gli strumenti concettuali e metodologici di base per impostare correttamente un disegno di ricerca sociologica, raccogliere e analizzare dati empirici, interpretare i risultati e comunicarli a diversi tipi di pubblico.
Expected learning outcomes
Al termine del corso, gli studenti saranno in grado di:
- Definire con precisione un problema di ricerca e formulare ipotesi empiricamente verificabili;
- Tradurre alcuni concetti teorici in variabili osservabili;
- Descrivere le principali strategie di raccolta dati;
- Identificare le fonti di dati 'micro' più adatte per specifici interrogativi di ricerca;
- Condurre analisi secondarie di dati micro-individuali in modo teoricamente orientato;
- Interpretare correttamente i risultati dell'analisi e comunicarli in modo chiaro ed efficace, sia in contesti accademici che extra-accademici.
- Definire con precisione un problema di ricerca e formulare ipotesi empiricamente verificabili;
- Tradurre alcuni concetti teorici in variabili osservabili;
- Descrivere le principali strategie di raccolta dati;
- Identificare le fonti di dati 'micro' più adatte per specifici interrogativi di ricerca;
- Condurre analisi secondarie di dati micro-individuali in modo teoricamente orientato;
- Interpretare correttamente i risultati dell'analisi e comunicarli in modo chiaro ed efficace, sia in contesti accademici che extra-accademici.
Lesson period: Second trimester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second trimester
Course syllabus
The course covers the following main topics:
1. The quantitative approach in social research: How to set up a research design and quantitative data analysis to answer questions and empirically test theoretically derived research hypotheses.
2. Sample surveys: Characteristics, potential, and limitations; Sampling strategies and basic statistical inference; Types of surveys (cross-sectional, longitudinal, panel, etc.); The main sources of micro data in Italy and Europe.
3. Secondary analysis: Introduction to secondary analysis; Data matrix and univariate analysis; Variable transformations, construction of indices and types; Bivariate analysis and simple linear regression; Logic of multivariate analysis; Interpretation and communication of results.
1. The quantitative approach in social research: How to set up a research design and quantitative data analysis to answer questions and empirically test theoretically derived research hypotheses.
2. Sample surveys: Characteristics, potential, and limitations; Sampling strategies and basic statistical inference; Types of surveys (cross-sectional, longitudinal, panel, etc.); The main sources of micro data in Italy and Europe.
3. Secondary analysis: Introduction to secondary analysis; Data matrix and univariate analysis; Variable transformations, construction of indices and types; Bivariate analysis and simple linear regression; Logic of multivariate analysis; Interpretation and communication of results.
Prerequisites for admission
Knowledge of elementary statistical analysis and the basic theoretical and practical elements of social research methodology is required. In particular, please refer to Corbetta, Piergiorgio. La ricerca sociale: metodologia e tecniche: II. Le tecniche quantitative. Il Mulino, 2015 - chapters I-IV.
Teaching methods
The classes will mix lectures and hands-on activities. We'll go over the main quantitative research and data analysis techniques using statistical software. There'll be lots of room for active participation: questions, critical discussions, and exercises in class or at home on real cases and data. The Ariel platform will be the main online teaching tool: slides, extra materials, and exercises will be uploaded weekly. The practical focus of the course is designed to encourage hands-on learning: attending students will develop a short group project based on secondary data analysis, which will also serve as a first step toward a future research thesis.
Teaching Resources
- slides and additional material uploaded on ARIEL
- Corbetta, P., Gasperoni, G., & Pisati, M. (2001). Statistica per la ricerca sociale. Bologna, Il mulino. [Chapters 1-7, 10]
- Biolcati-Rinaldi F. e Vezzoni C. (2012), L'analisi secondaria nella ricerca sociale. Bologna: Il Mulino [Chapters 1, 2, 4]
- Corbetta, P., Gasperoni, G., & Pisati, M. (2001). Statistica per la ricerca sociale. Bologna, Il mulino. [Chapters 1-7, 10]
- Biolcati-Rinaldi F. e Vezzoni C. (2012), L'analisi secondaria nella ricerca sociale. Bologna: Il Mulino [Chapters 1, 2, 4]
Assessment methods and Criteria
Attending students (attendance at least 80% of classes):
1) Test (60% of the assessment): multiple-choice questions aimed at verifying understanding of the fundamental concepts of the course and assessing the achievement of the educational objectives listed above.
2) Final group project (40% of the assessment): secondary analysis of micro-individual data to answer a research question. The work will be assessed on: structure and clarity of presentation, formulation of hypotheses, choice and description of data and methods, quality of analysis, interpretation, and discussion of results.
Non-attending students:
1) Test in two parts: (i) multiple-choice questions to check your understanding of the main ideas of the course and see if you've hit the learning goals above (60% of the grade); (ii) short exercises on univariate and multivariate analysis (40% of the grade).
1) Test (60% of the assessment): multiple-choice questions aimed at verifying understanding of the fundamental concepts of the course and assessing the achievement of the educational objectives listed above.
2) Final group project (40% of the assessment): secondary analysis of micro-individual data to answer a research question. The work will be assessed on: structure and clarity of presentation, formulation of hypotheses, choice and description of data and methods, quality of analysis, interpretation, and discussion of results.
Non-attending students:
1) Test in two parts: (i) multiple-choice questions to check your understanding of the main ideas of the course and see if you've hit the learning goals above (60% of the grade); (ii) short exercises on univariate and multivariate analysis (40% of the grade).
Educational website(s)
Professor(s)