Data Lab
A.Y. 2020/2021
Learning objectives
Undefined
Expected learning outcomes
Undefined
Lesson period: First trimester
Assessment methods: Giudizio di approvazione
Assessment result: superato/non superato
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
First trimester
Course syllabus
First part (prof. Ballarino):
Introduction to quantitative analysis.
Variable types, centrality measures.
Dispersion measures and frequency distributions.
Central limit theorem and the logic of inference.
Bivariate analysis (crosstabs and mobility tables, correlation and differences in means).
Second part (prof. Panichella):
The logic of test and t-test.
The logic of multivariate analysis (controls and interactions).
Regression model and regression function.
OLS regression models.
Model specification and interpretation
Introduction to quantitative analysis.
Variable types, centrality measures.
Dispersion measures and frequency distributions.
Central limit theorem and the logic of inference.
Bivariate analysis (crosstabs and mobility tables, correlation and differences in means).
Second part (prof. Panichella):
The logic of test and t-test.
The logic of multivariate analysis (controls and interactions).
Regression model and regression function.
OLS regression models.
Model specification and interpretation
Prerequisites for admission
Basic knowledge of math
Teaching methods
Frontal lessons
Teaching Resources
Agresti, A. and Finlay, B. Statistical Methods for the Social Sciences, fifth edition, Pearson Global Edition. Chapters: 1, 3, 5, 6, 8, 9, 14.
Additional readings:
Mehmetoglu, M., & Jakobsen, T. G. (2016). Applied statistics using Stata: a guide for the social sciences. Sage.
Bernardi, F., Chakhaia, L., & Leopold, L. (2017). 'Sing me a song with social significance': The (mis) use of statistical significance testing in European sociological research. European Sociological Review, 33(1), 1-15.
Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political analysis, 14(1), 63-82.
King, G., Tomz, M., & Wittenberg, J. (2000). Making the most of statistical analyses: Improving interpretation and presentation. American journal of political science, 347-361
Nagler, J. (1995). Coding Style and Good Computing Practices. PS: Political Science & Politics, 28(03), 488-492.
Additional readings:
Mehmetoglu, M., & Jakobsen, T. G. (2016). Applied statistics using Stata: a guide for the social sciences. Sage.
Bernardi, F., Chakhaia, L., & Leopold, L. (2017). 'Sing me a song with social significance': The (mis) use of statistical significance testing in European sociological research. European Sociological Review, 33(1), 1-15.
Brambor, T., Clark, W. R., & Golder, M. (2006). Understanding interaction models: Improving empirical analyses. Political analysis, 14(1), 63-82.
King, G., Tomz, M., & Wittenberg, J. (2000). Making the most of statistical analyses: Improving interpretation and presentation. American journal of political science, 347-361
Nagler, J. (1995). Coding Style and Good Computing Practices. PS: Political Science & Politics, 28(03), 488-492.
Assessment methods and Criteria
Written exam
SPS/04 - POLITICAL SCIENCE - University credits: 3
Laboratories: 20 hours
Professors:
Ballarino Gabriele, Panichella Nazareno
Professor(s)
Reception:
Wednesday h 9-12 am. It is possible to make an appointment for other timings by writing an e-mail to [email protected]
Dept. of Social and Political Science, Room 5 first floor (above the cafeteria)