The project uses data analytics to examine factors influencing student spending behavior. A structured simulated dataset of student income and expense categories was created using reasonable parameters based on publicly available student spending information and budgeting references. Public datasets did not contain the specific combination of variables and categories required for the research scope, so simulation was used to create a dataset suitable for analysis. The project applies statistical analysis, data visualization, and regression techniques to identify spending patterns and relationships between income and expenses. The findings provide practical insights to help students better understand spending behavior and improve financial decision-making.
