Date of Award

5-2025

Document Type

Project

Degree Name

Master of Science in Business and Data Analytics

Department

College of Business and Public Administration

First Reader/Committee Chair

Daniel Macdonald, Ph.D

Abstract

The purpose of this project is intended to investigate the lack of use of data analytics in predicting and managing the impacts of economic crises. This project investigates what economic key factors can be used to create a framework model and evaluate the effectiveness of the key economic indicator being tested as early warning signs. The project uses programs such as Excel, RStudio, and Tableau for the collection of historical data, and regression analysis to determine if certain economic indicators have a statistically significant correlation with GDP, that may help enforce systems in place to help us mitigate economic crises in the future. Analyzing previous economic crises, such as the Great Depression, the Great Recession and the COVID-19 pandemic, I explore the statistical relationship between variables such as unemployment rates, business applications, CPI, exports and import against GDP, revealing some significant economic indicators. The data revealed unemployment and inflation may be economic indicators, we can use them as early signs to predict early warnings. This paper also emphasizes mental health impacts associated with the economic crisis and the need to study this field more in depth. TThis study continues to underscore the need for comprehensive proactive policies and the integration of data-driven models to enhance our crisis preparedness to ensure a resilient economy and protect societal well-being.

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