Essentials of Applied Data Analysis

Leonardo S. Barone


This course is designed for students who are interested in reviewing their training in statistics. It prepares students for courses offered in the IPSA-USP Summer School that require statistical training.  It reviews basic probability; random variables and their distributions; confidence intervals and tests of hypotheses for means, variances, and proportions from one or two populations. To complement lectures, students apply the concepts taught in lectures to analyze problems using Excel and Stata.   


This course runs January 14-18, 2019.

TEACHING FELLOW:  Flávio Souza, Texas A&M University


This course departs from the premise that the most effective way to learn statistics is by actively engaging in doing the statistical analysis. For each topic, we will have lectures that will be followed by sessions in which students will use data to answer questions that are important to political scientists. Although the goals of the class are primarily conceptual rather than narrowly mathematical, students should feel comfortable with engaging with mathematics, formulas, and data analysis.

By the end of the intensive one-week course, students should be able to apply basic concepts in probability theory to social science research questions, to make inferences about the distribution of populations based on a sample and to correctly conduct and interpret hypothesis tests. For those students who will be studying multivariate regression analysis in the Summer School, the course will provide an intuitive and basic review of linear regression in theory and practice.


The course presumes students have some basic training in mathematics including arithmetic and algebra operations.