B6165 - RESEARCH METHODS

Learning outcomes

The course introduces students to graduate levels tools to analyze empirically political and social phenomena and design data driven policies. At the end of the course students 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

Quantitative data analysis plays a foundational role in social and political science research, shaping academic articles, books, and public discourse—from election polls to reports on tourism, crime, or migration trends. It also underpins evidence-based policy design and government decision-making. For social scientists—and informed citizens alike—developing the ability to interpret and critically evaluate quantitative research findings is essential.

This course provides an introduction to the logic and practice of social science research, with a focus on quantitative methods and statistical reasoning. Students will learn how to design feasible and relevant research questions and identify the most appropriate analytical strategies based on available data and research design. Topics covered include the transition from theory to empirical research (e.g, operationalization of concepts), the construction and use of surveys, scaling techniques, sampling strategies, univariate and bivariate description of data (e.g., measures of central tendency and variation, contingency tables), basic inferential statistics (e.g., hypothesis testing), and regression analysis (linear and logistic).

A key component of the course is training in data analysis using the statistical software Stata. Weekly lectures introduce core concepts while lab sessions apply these tools through hands-on exercises. These practical sessions cover data management, scaling and indices, descriptive statistics, regression models, and more, following a learning-by-doing approach. Students are encouraged to develop a personal research question and will work with secondary data to explore it, applying various analytical techniques and learning to effectively visualize and communicate their findings.

In addition to the core curriculum, seminars led by guest researchers will introduce advanced methods—such as social network analysis and panel data techniques—demonstrating their application in ongoing research projects.

Attendance is strongly encouraged but not compulsory.

There are no formal prerequisites for the course. However, familiarity with basic descriptive statistics and introductory experience with statistical software (such as Stata, SPSS, or R) is beneficial.

The detailed syllabus, including the full schedule of lectures, labs, and seminars, will be available on Virtuale prior to the start of the course. Please remember to enroll before the start of the lectures on https://virtuale.unibo.it/

Readings/Bibliography

Available as ebook on SBA Almastart

Corbetta, P. (2003). Social research: Theory, methods and techniques. London: SAGE

Hanneman, R. A, Kposowa, A. J, Riddle, M. D. (2013) Basic Statistics for Social Research. San Francisco, CA: Jossey-Bass.

Agresti, A., Franklin, C. A, Klingenberg, H. (2018). Statistics: the art and science of learning from data. Englan: Pearson.

Teaching methods

The course comprises lectures, Stata labs, and seminars with invited speakers.

Assessment methods

The final grade for the course is entirely based on a computer-based exam, held in one of the university's computer labs. The exam accounts for 100% of the final grade and includes both theoretical questions and practical exercises using the Stata software.

Students will be required to demonstrate their understanding of key concepts in research design and statistical analysis, as well as their ability to apply these methods in practice through basic data manipulation, analysis, and interpretation within Stata.

Internet access will not be available during the exam; however, all necessary tools and datasets will be provided in advance or during the session.

When students repeat the exam, only the last grade earned is counted. Please notice that, according to the University regulations, a passing-grade can be refused only once.

Teaching tools

Students should bring their laptop to the lectures. If this is not possible, let the instructor know as soon as possible.

Before the start of the course, students are expected to:

- enroll on the course Virtuale space https://virtuale.unibo.it/

- Download the software Stata https://www.unibo.it/en/services-and-opportunities/studying-and-beyond/discounts-for-computer-tablet-and-software-1/stata-se-campus-licence

- Register on the European Social Survey website https://ess-search.nsd.no/

Students with learning disorders and\or temporary or permanent disabilities: please, contact the office responsible (https://site.unibo.it/studenti-con-disabilita-e-dsa/en/for-students ) as soon as possible so that they can propose acceptable adjustments. The request for adaptation must be submitted in advance (15 days before the exam date) to the lecturer, who will assess the appropriateness of the adjustments, taking into account the teaching objectives.

Office hours

See the website of Francesca Zanasi