Análise de componentes principais e ajustes de funções aos dados de COVID-19

Abstract

In this work it is defined what are principal components of multivariate data as well as their importance, their properties and their applications. We will then analyze the possibility of applying the PCA to Covid-19 data obtained through SEADE (Sistema Estadual de Análise de Dados Estatísticos) we also explored in detail some function adjustments to the data in order to make some pertinent observations and presented the SIR (Susceptible, Infected and Recovered) model for exploring diseases. For the reader’s better understanding, we use some basic concepts in the first chapter, which are useful throughout the rest of the work.