Inspiration: The percentage of uninsured population differs significantly by states.
What it does: Our project makes two hypotheses and found that college education and population wealth are two factors affecting uninsured rate.
How we built it: We built the the linear regression models with R and made visualizations with Tableau.
Challenges we ran into: Finding out what could possibly be the predictor of uninsured rate was challenging.
Accomplishments that we're proud of: Cooperated as a group efficiently and communicated respectfully with each other throught the entire project.
What we learned: We learned methods of extracting data from a dataset, analyzing the underlying relationships and presenting what we found through visualization.
What's next for Healthcare Data Analysis: People's awareness of the importance of insurance needs to be strengthened.
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