METHODOLOGIES FOR THE SOCIAL SCIENCES II: QUANTITATIVE (INTRODUCTIVE COURSE)

Period of duration of course
‌‌
Course info
Number of course hours
20
Number of hours of lecturers of reference
20
CFU 3
‌‌

Modalità esame

Take-home exam: pass/fail for PhD students; graded on a 30-point scale for MA students.

Note modalità di esame

The exam will consist of short questions covering key contents of the course and a practical exercise with STATA/interpretation thereof. It will not require any knowledge of calculus or mathematics beyond simple arithmetic. Class attendance and participation are mandatory.

Prerequisiti

Compulsory for first year PhD students. Optional for all MA students.

Programma

This course is meant to provide a general introduction to quantitative data analysis for social and political science research. It assumes no prior (or very basic) knowledge of statistical methods and quantitative techniques. It will combine theoretical foundations of quantitative designs with a practical, hands-on approach— for this purpose, the statistical software STATA shall be used.

The course will start from the basics of quantitative analysis, covering key concepts and features, types of variables and datasets. After that, it will address descriptive statistics. It will then deal with the main aspects of linear regression analysis: assumptions, estimations, practical application to research questions and examples, presentation of results and interpretation. The course will conclude by giving an overview of other types of regressions that participants might need to use in their future research. At the end of this course, participants will be able to understand the theoretical background of the most basic statistical techniques and select the appropriate method for their research question; learn how to organize a dataset and perform basic quantitative analysis (including descriptive tables and graphs) as well as linear regressions; they will be able to meaningfully interpret the results of these methods; and how to use the software STATA for data analysis.

Obiettivi formativi

At the end of this course, participants will be able to understand the theoretical background of the most basic statistical techniques and select the appropriate method for their research question; learn how to organize a dataset and perform basic quantitative analysis (including descriptive tables and graphs) as well as linear regressions; they will be able to meaningfully interpret the results of these methods; and how to use the software STATA for data analysis.

Riferimenti bibliografici

Key references:

Acock, A. C. (2018). A Gentle Introduction to STATA. College Station, TX: Stata Press.

Lewis-Beck, C. & Lewis Beck, M. (2016). Applied Regression: An Introduction. Thousand Oaks, CA: SAGE.

Treiman, D.J. (2009). Quantitative Data Analysis: Doing Social Research to Test Ideas. San Francisco, CA: Jossey-Bass.

  

Additional resources:

-        Quant Methods for the Social Sciences, Prof Gary King https://www.youtube.com/playlist?list=PL0n492lUg2sgSevEQ3bLilGbFph4l92gH

-         UCLA module for STATA https://stats.oarc.ucla.edu/stata/modules/

-         Princeton’s online STATA tutorial https://www.princeton.edu/~otorres/Stata/

-         Gordon, R. A. (2015). Regression Analysis for the Social Sciences. London: Routledge, 2nd ed.

-         Imai, K., & Bougher, L.D. (2021). Quantitative Social Science: An Introduction in Stata. Princeton, NJ: Princeton University Press.