This analysis explores classification techniques for predicting qualitative responses, focusing on the reactivity of elements based on their atomic properties. Unlike regression models, which predict quantitative outcomes, classification assigns observations to categories or classes. In this project, I aimed to classify elements from the periodic table as reactive (Yes = 1) or non-reactive (No = 0) based on their properties.

In this project we have presented an analysis of global education data on completion rates across different demographic categories, including gender, wealth quintiles, residence (urban vs. rural), and time periods. The study uncover patterns and disparities that could inform targeted policy interventions, NGO initiatives, and education reforms at both regional and international levels.

Trabalho individual da discente Maria Fernanda Nunes Pinheiro Barbosa, realizado na disciplina NUT105 Bioestistica do programa de Pós Graduação em Saúde e Nutrição da UFOP, ministrada pelo professor Marcelo Carlos Ribeiro