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Major
Business Administration
Anticipated Graduation Year
2022, 2023
Access Type
Open Access
Abstract
We conducted this research study in hopes of finding a correlation between consumer spending in various retail sectors and the sum of new COVID-19 cases in the United States. We used the random decision tree model, a data mining tool that compares different factors and determines the importance they have in predicting an outcome (or target), to find connections in our data. The results of this study can be used by businesses or governments to see where consumer sentiment is shifting and how they can adapt their business or political strategies in the case of future pandemics or other extraordinary worldwide events.
Faculty Mentors & Instructors
Professor Carolyn Kmet
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 3.0 License.
Consumer Spending as a Predictor for COVID-19
We conducted this research study in hopes of finding a correlation between consumer spending in various retail sectors and the sum of new COVID-19 cases in the United States. We used the random decision tree model, a data mining tool that compares different factors and determines the importance they have in predicting an outcome (or target), to find connections in our data. The results of this study can be used by businesses or governments to see where consumer sentiment is shifting and how they can adapt their business or political strategies in the case of future pandemics or other extraordinary worldwide events.