COVID-19 Data Analysis
This project is a data analysis that explores COVID-19's relationship & impact on various aspects across different US states. It covers topics ranging from economic to social and political spheres, analyzing data sourced from multiple outlets, including worldpopulationreview.com. The data was managed by adjusting values to a scale of "per 100K people." Queries and hypotheses were posed and analyzed, addressing questions such as the correlation between state politics and COVID-19 cases, the impact of COVID-19 on businesses, and the relationship between COVID-19 and unemployment.
Project information
- Category: Probability & Statistics
- Completion Date: April 17, 2021
- Technologies Used: Tableau, OpenMarkov, BigML, Miniab, Excel
- Presentation URL: COVID-19 Data Analysis
Insights derived from the analysis reveal intriguing findings, such as the influence of mask mandates on COVID-19 cases and the negligible impact of marijuana legalization on case numbers. The presentation provides detailed analyses of various queries and hypotheses, supported by visual aids created using tools like Tableau and OpenMarkov. It delves into specific aspects like the correlation between governor and election partisans and COVID-19 cases, the impact of mask mandates on case numbers, and the relationship between marijuana legalization and COVID-19 outcomes. Conclusions drawn from the analyses suggest that while political affiliations may have minor effects on case numbers, mask mandates play a significant role in reducing COVID-19 transmission. Additionally, the presentation highlights the need for further research and policy interventions to mitigate the spread of the virus effectively.