Tutorial Project: Credit Card Application Data Analysis - FDS

This tutorial project focuses on analyzing a credit card application dataset, covering techniques from the Foundations of Data Science course. The project begins by importing data from a public source, handling missing values, and assigning variable names and types. It then explores proximity measurements using the Gower distance, visualizing the data relationships through distance matrices and heatmaps. The analysis includes calculating Pearson and Spearman correlation matrices for numerical variables. The project aims to explore the data patterns and relationships. The project uses the R programming language for data manipulation, analysis, and visualization. The project's objective is to apply and explore the techniques covered in the initial weeks of the Foundations of Data Science subject, providing practical experience in data handling and analysis.