Data Analysis and Statistics

A.Y. 2020/2021
6
Max ECTS
40
Overall hours
SSD
SECS-S/03
Language
English
Learning objectives
The increasing availability of data allows to analyse several issues related to social, labour and organizational dynamics. The course aims to introduce the logic of theory-driven statistical analysis in social research, providing useful tools for data manipulation, exploratory data analysis, statistical test, categorical data analysis, and regression.
The course consists of both theoretical lessons, where the main statistical techniques are introduced, and empirical lessons, where techniques are empirically implemented (learning by doing). Lessons are coupled with 20 hours of lab, aiming to consolidate the topics of the classes and to work on the students' final research.
Expected learning outcomes
At the end of the course, students will be able to conduct multivariate analyses and to apply the basic principles of statistical inference. Moreover, students will be able to use the statistical software STATA and to conduct autonomously a research project, with the aim of informing conclusion and supporting decision-making. Finally, students will be able to interpret scientific contributions based on statistical multivariate analysis, considering both the potentials and the limitations of data analysis.
In detail, students will:
- collect data and enter their own datasets for analysis;
- identify appropriate statistical methods;
- conduct their own analysis using the software program STATA;
- interpret the results of the data analysis;
- check the assumptions on which each analysis depends and make appropriate adjustments or select alternative methods of analysis.
Course syllabus and organization

Single session

Responsible
Lesson period
First trimester
There will be two weekly lessons: a theoretical one, which will take place remotely, and a practical one that will instead be held in the classroom.
The exam will be written and includes a theoretical and a practical part. In the latter, students have to answer some research questions using the statistical software STATA
Course syllabus
Introduction to quantitative analysis, variable types, centrality measures. Dispersion measures and frequency distributions. Probability, central limit theorem, the normal distribution and the concept of standard error. Student's T distribution and its relationship with other distributions. The logic of a test and t-test. T-test assumptions. Bivariate analysis - Crosstabulations P-values and Chi-square test, Correlation, simple OLS regression. Introduction to multivariate analysis, introduction to multiple OLS regression models, introduction to Linear probability models.
Prerequisites for admission
Basic knowledge of math
Teaching methods
There are two types of class: the theoretical lessons introduce students to the main statistical techniques, while the practical lessons introduce participants to the use of Stata to analyse quantitative datasets.
Lectures will be coupled with 20 hours of lab, aiming to consolidate the topics of the classes. .
Teaching Resources
Agresti, A. and Finlay, B. Statistical Methods for the Social Sciences, fourth edition, Pearson International Edition.

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
The exam will be written and includes a theoretical and a practical part. In the latter, students have to answer some research questions using the statistical software STATA
SECS-S/03 - ECONOMIC STATISTICS - University credits: 6
Lessons: 40 hours
Professor(s)
Reception:
Monday, 14.30-17.30
Room 1