90892 - Data Analysis For The Social Sciences

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 2021/2022

Learning outcomes

The course deals with topics concerning the methodology of socio-political empirical research and addresses statistical data analysis techniques. Students who have completed this course will be able to: a) examine the pros and cons of the main data collection designs; b) explore quantitative data and interpret empirical results; c) analyze quantitative datasets resorting to statistical software; d) define a research problem, formulate research questions, collect data, test research hypotheses empirically, draw conclusions, and communicate research results.

Course contents

The course is for students who have never studied topics concerning key concepts underlying social research techniques, neither theoretically nor empirically.

The course aims to illustrate the debate about social science methodology and the most common data collection and analysis strategies in the field of socio-political empirical research. Lessons will address the following topics: the logic of social research; standard and non-standard approaches to social research; operationalization and operational definitions; concepts and indicators; types of property and types of variable; displaying social research results; basic (descriptive) monovariate and bivariate statistical analysis.

Readings/Bibliography

The two basic texts are the following:

Corbetta P., Social Research. Theory, Methods and Techniques, London, Sage, 2003: Chapters 1, 2, 3, 4, 5, 6, 8, 9, 10, 11 (i.e., all but 7).

Bohrnstedt G.W. and Knoke D., Statistics for Social Data Analysis, Peacock, 1982 (1st. ed.): Chapters 2, 3, 4, 8 (up to and including 8.5), 9, Appendix A (in the 1982 edition) [social research process / frequency distributions / describing frequency distributions / crosstabulation / estimating relations between two continuous variables / measuring association with discrete variables / use of summations]. Contact prof. Gasperoni if you are using other editions with different tables of contents.

 

Teaching methods

Face-to-face lectures.

Additional workshop activities using Stata software for data analysis.

Attendance is strongly recommended.

Assessment methods

Starting June 1, 2022, the exam is administered in exclusively *written* form and *in person* (on-line exams are no longer contemplated). The only valid mark is the one achieved in the most recent attempt to pass the exam. Candidates who do not participate in an exam for which they have registered cannot participate in the following exam session. Students can refuse a passing mark just one time.

Exam modes may change in light of the ongoing Covid19 public health emergency.

Please note that Art. 25, Paragraph 2 of the Code of Ethics and Conduct of the University of Bologna requires that "in course exams and degree programme final exams, students must refrain from conduct that may cause disturbance or obstacle or involve harmful and/or dishonest consequences towards other students and the institution. Plagiarism or copying of other people's texts or other behaviours that hinder a correct evaluation of exam performances are contrary to the principles of this Code”.

Office hours

See the website of Giancarlo Gasperoni