- Docente: Giancarlo Gasperoni
- Credits: 8
- Language: Italian
- Teaching Mode: Traditional lectures
- Campus: Bologna
-
Corso:
Second cycle degree programme (LM) in
Public and Corporate Communication (cod. 8840)
Also valid for Campus of Forli
Second cycle degree programme (LM) in International relations and diplomatic affairs (cod. 8783)
Second cycle degree programme (LM) in Politics Administration and Organization (cod. 8784)
Second cycle degree programme (LM) in International Relations (cod. 8782)
Second cycle degree programme (LM) in Local and Global Development (cod. 9200)
Learning outcomes
The course addresses statistical data analysis techniques. Students are expected to have previously acquired basic skills in social and political research methodology. Upon successfully completing the course, students should be proficient in the basic techniques for bivariate descriptive analysis of data collected in data matrices; understand the main principles of statistical inference; be familiar with the key features of multivariate statistical analysis; be able to interpret results of multivariate models; grasp the chief sampling techniques; can critically evaluate data analyses performed by other scholars; knows how to access statistical data sources.
Course contents
The course provides an in-depth overview of statistical analysis techniques, aims to promote students' ability to interpret and critically evaluate statistical information, and provides specific skills for the autonomous processing of information gathered in a data matrix. By the end of the course, student will be able to read and understand articles in specialized publications containing statistical analysis results; evaluate statistical summaries and processing of census or sampling data; autonomously apply a selection of statistical analysis techniques for the description of economic, political and social phenomena; know the basics of inferential statistics. In particular, teaching will focus on bivariate and multivariate analysis techniques and will also have a practical component focusing on the use of spreadsheets (Excel) and / or other software dedicated to data processing.
Students should already be well-versed in sociological / political science methodology and basic elements of statistics. If the student is not in possession of suck skills knowledge, attendance of Social and Political Research Methodology (course no. 78074) is strongly recommended.
As to the basic elements of statistics, at the very least a careful reading of the following text is required: P. Corbetta, G. Gasperoni and M. Pisati, Statistica per la ricerca sociale, Bologna, Il Mulino, 2001 (chapters 1-3) .
Readings/Bibliography
Reference texts (for both attending and non-attending students) are the following:
Corbetta, Piergiorgio, Giancarlo Gasperoni and Maurizio Pisati, Statistica per la ricerca sociale, Bologna, Il Mulino, 2001 (chapters 4-10).
[corrections to printed text available in AMS Campus]
Blalock, Hubert M., Jr., Statistica per la ricerca sociale, Bologna, Il Mulino, 1984 (only part 3, dealing with inductive statistics, i.e., chapters 8, 9 10, 11 and 12.
[available in AMS Campus]
The first text can be supplemented (not replaced) by the following:
Terraneo, Marco, Studiare e controllare le relazioni: l’analisi bivariata e la terza variabile, chapter 7 in Antonio de Lillo et alii, Metodi e tecniche della ricerca sociale, Milano-Torino, Pearson, 2011, pp. 307-378.
Argentin, Gianluca, La regressione multipla, chapter 2 in Antonio de Lillo et alii, Analisi multivariata per le scienze sociali, Milano, Pearson, 2007, pp. 13-53.
[corrections to the printed text availablein AMS Campus]
Sarti, Simone, La regressione logistica, chapter 3 in Antonio de Lillo et alii, Analisi multivariata per le scienze sociali, Milano, Pearson, 2007, pp. 55-90.
[corrections to the printed text available in AMS Campus]
Bohrnstedt, George W. and David Knoke, Statistica per le scienze sociali, Bologna, Il Mulino, 1998, chapters VI, VII, VIII, IX.
The second text (Blalock) can be supplemented (not replaced) by the following:
Bohrnstedt, George W. and David Knoke, Statistica per le scienze sociali, Bologna, Il Mulino, 1998, chapters III.
Teaching methods
Face-to-face lessons and practical exercises. Attendance is strongly recommended.
Assessment methods
The exam is administered in exclusively written form. The only valid mark is the one achieved in the most recent attempt to pass the exam. A candidate who doesn't participate in an exam for which he/she has registered cannot participate in the following exam session.
Office hours
See the website of Giancarlo Gasperoni