The objective of this project is to explore and analyze purchasing patterns recorded in the Online Retail Dataset. I aim to apply multivariate analysis techniques to: Identify customer groups based on purchasing behaviors. Explore the relationship between different variables, such as quantity purchased, price, and purchase frequency. Discover product associations to recommend items frequently bought together. To achieve this, we use multivariate analysis techniques such as: Discriminant Analysis Principal Component Analysis (PCA) Cluster Analysis

Exploratory Analysis of Time Series, applying SARIMA modeling, and making predictions

Criação de uma função para calculo de intervalos de confiança para razões entre variâncias