- Docente: Nicola De Luigi
- Credits: 5
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Forli
- Corso: First cycle degree programme (L) in Sociology (cod. 8495)
Learning outcomes
Participation in the workshop allows the student to discover one of the advanced methods for the analysis of data (numeric or text) in the social sciences, and learn how to apply trough the main software available. At the end of the workshop path the student is able to build a data matrix, predispose the information processing, realize analysis and interpreting the results thereof. Because learn to use software for analysis information so aware (of the theoretical and methodological choices that guide the technical aspects) takes time and application, this workshop each year will focus on a theme, so as to enable the participants to come to acquire the techniques presented in a fair and be able to apply operationally independent way.
Course contents
The course activities are structured in two parts.
The first part proposes an in-depth itinerary concerning the following topics: research design, conceptualisation and measurement (operational definitions), questionnaire development (writing questions), data collection and data matrix and data analysis (relationships among variables).
The second part aims to introduce students to data analysis by means of dedicated statistical analysis software.
Readings/Bibliography
P. Corbetta, La ricerca sociale: metodologia e tecniche II. Le tecniche quantitative, il Mulino, Bologna, 2003 (capitoli I, III, IV e V).
P. Corbetta, La ricerca sociale: metodologia e tecniche IV. L’analisi dei dati, il Mulino, Bologna, 2003.
N.B. Students may choose to prepare coursework relevant to the work carried out during the course. This must be approved by the teacher.
Teaching methods
Face to face lessons.
The course also provides an introduction to statistical software packages for research in social sciences (i.e. Stata and SPSS) and practice exercises to set up data files, manipulate variables and run statistical programs.
Assessment methods
Assessment will be in both written (in-class exercises) and oral form.
Class attendance and regular participation is required for this course.
Teaching tools
Lessons will be held in computer lab and students will access to SPSS
Office hours
See the website of Nicola De Luigi