QUALITATIVE AND QUANTITATIVE METHODOLOGIES FOR SOCIAL SCIENCES

In social sciences, the capacity to produce rigorous empirical evidence depends on the integrated mastery of both quantitative and qualitative methodologies. Informed by a research-driven and problem-solving oriented logic, this course equips students with the methodological toolkit required to design, conduct, and critically evaluate empirical inquiry in social and economic contexts, where research questions increasingly demand the triangulation of measurement and meaning. The course explores the foundations and applications of empirical research in the social sciences along two complementary axes. On the quantitative side, it covers the statistical analysis of univariate and multivariate data, with particular emphasis on social and economic applications: descriptive techniques, inferential reasoning, regression-based modelling, and the interpretation of statistical evidence in light of substantive research questions. On the qualitative side, it introduces students to data collection through interviews and observation, the coding of textual material, and strategies for the systematic integration of qualitative evidence into broader empirical analysis. The course combines the transfer of academic knowledge with the acquisition of inquiry-based skills. Students will engage in a Project Work, through which they will be asked to design and develop an original empirical study on a research question of their choice, mobilizing both quantitative and qualitative tools acquired during the course. During the semester, students will be guided in progressively turning their research design into a structured research output, learning by experimenting with methodological rigor, transparency, and replicability.

Basic concepts of Mathematics and Epistemology.

Students will be able to understand basic principles of scientific inquiry in social sciences, interpret qualitative and quantitative results, and distinguish between descriptive, associative, and causal claims. The course also develops the ability to choose appropriate methods depending on the research question and data type, recognizing when to apply qualitative or quantitative approaches. Quantitative data analysis will be conducted using R, which is an essential component of the course.

Quantitative part Basic concepts of statistics Different types of data Exploratory and descriptive data analysis Linear regression model Generalized Linear Models Network analysis Natural Language Processing Scripting in R Qualitative part epistemology of social research qualitative research design data collection data analysis writing qualitative findings

Lecturer’s slides Hurst, Allison. (2023). Introduction to Qualitative Research Methods: A Helpful Guide for Undergraduates and Graduate Students in the Social Sciences. Oregon State University. https://open.oregonstate.education/qualresearchmethods/ Before each lesson the students are expected to read the mandatory reading(s). Unless covered by copyright restrictions, mandatory readings are available via the Luiss Learn on-line platform. Compliant students students must refer to the mandatory readings; non-compliant and exempted students must consider also supplementary readings as mandatory.

Theory and computer lab lectures. Slides and scripts will be made available to the students.

The assessment for compliant students is based on: a group project worth 30% of the final grade, with grades released in Week 11; a final written exam worth 70% of the final grade, consisting of: multiple-choice and open-ended questions for the qualitative part. Non-compliant and exampted students will take a final written exam accounting for 100% of their final grade. The exam will include additional questions compared to those for compliant students and will also cover supplementary readings. Note: Plagiarism and academic dishonesty are strictly prohibited. Any suspected violations will be handled according to standard LUISS University procedures.

Obtaining a grade above 29/30. Then, thesis assignment is based on a project presented by the student. The project (2/3 pages) must include: • Table of contents • Abstract • Main references