81769 - Method and Data Analysis Techniques (pari)

Course Unit Page

SDGs

This teaching activity contributes to the achievement of the Sustainable Development Goals of the UN 2030 Agenda.

Quality education

Academic Year 2018/2019

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 Materiali didattici]

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 Materiali didattici]

 

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 available in Materiali didattici]

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 Materiali didattici]

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. 

Candidiates who pass the exam can refuse the final mark (thus requesting to re-take the exam) only once, in accordance with the university's teaching regulations. After having rejected a passing mark, any other subsequent passing mark will be recorded definitively in candidates' transcipts.

Office hours

See the website of Giancarlo Gasperoni