Credit Card Application Analysis: Data Science Tutorial Project

This tutorial project for the Foundations of Data Science subject focuses on analyzing credit card application data. The project begins with importing data from a publicly available source and handling variable types, names, and missing values using R programming. It then proceeds to calculate and visualize proximity measurements using the Gower dissimilarity index and distance matrices. The project includes code for importing the data, defining variable types, removing missing values, calculating Gower distances, converting to a distance matrix, and visualizing the matrix. The analysis involves discussing the symmetry of binary variables, calculating Gower similarity, and interpreting the resulting visualizations, including a heatmap of the distance matrix and correlation plots. The project aims to explore data structures and relationships within the credit card application dataset, providing insights into potential factors influencing credit approval decisions. The student has provided the R code and analysis for each step of the project, including interpreting the patterns observed in the visualizations.