Socio-economic, cultural, and environmental influences on COVID-19 pandemic outcome -- excess mortality
This is a capstone research project for the Certificate in Applied Data Science (CADS) at my undergraduate institution, Wesleyan University, on the topic of "Understanding the Variances in COVID-19 Pandemic Outcome - Excess Mortality - with Social, Cultural, and Environmental Factors".
- AUTHOR: Jiner Zheng
- FACULTY SPONSOR: Prof. Maryam Gooyabadi
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DTW.Rmd contains code for data cleaning, data management, functions of producing excess deaths using ARIMA/GARCH, & implementations of hierarchical clustering analyses on Time Series data based on Euclidean distances and Dynamic Time Warping (DTW) distances.
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K-medoids.Rmd contains code for implementing K-Medoids clustering on mix-typed data with computations of the Gower distance.
Note: you can also set up the environment using JZ-capstone.Rproj in R.
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JZ-capstone.pdf contains my presentation slides outlining our literature reviews, measures and analytical methods, findings, and recommendations.
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JZ_CADS_capstone_spring2022.pdf is the final paper of this presented work.