Gustavo Arruda Franco's repositories
Homework-7
Basic machine learning methods. One is a random forest model used to choose among categorical variables from the GSS to predict attitudes towards racist college professors, the other is a backwards selection algorithm to choose variables to predict student debt. Produced for the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Data-Analysis-Samples
Some samples of data analysis projects I have done before. Includes computational textual analysis of religious responses to COVID in Brazil, and exploratory data analysis of support to democracy variables broken down by religion in the Latinobarometro survey.
Homework-1
Intro section about me showing initial GitHub skills for the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-2
Data visualization of mass shootings in the United States. Produced within the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-3
Data visualization of Supreme Court decisions, with additional wrangling exercises. Produced within the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-4
Exploration and visualization of World Bank Indicators dataset, focusing on military expenditure and inequality, with additional programming exercises. Produced within the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-5
Practice in debugging an R script analyzing historical data of baby names in the United States, and practice in creating parameterized MarkDown reports analyzing each country's HIV data. Produced within the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-8
Visualizations made of data scraped from tables on the website of the Brazilian Congress, and visualizations made of data retrieved from the Geonames API. Produced for the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Measurement
Psychometric techniques, including functions to analyze dichotomous variables, and applied examples of factor analysis and discriminant analysis. Produced within the classes "Principles and Methods of Measurement" and "Public Opinion", both taught at the University of Chicago in the Spring of 2021.
Homework-6
Independent data analysis of religious variables in the Latinobarometro survey. Produced within the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.
Homework-9
Probabilistic topical modelling of textual data about COVID that I collected from Brazilian religious institutions in 2020. Produced for the course "Computation for the Social Sciences", offered during the Fall of 2020 at the University of Chicago.