Understanding Seasonality of Deaths in Relation to Age Group

Inspiration

I was inspired by my initial graph of the data on deaths in the 50 states. I wanted to understand the patterns that could be held there.

What it does

The predictive model I created is trained by the data to predict how many deaths will occur in the future due to the three diseases per month.

How we built it

I built my initial visualizations using Tableau to understand the data better, and then I used R to find the correlation as well as create the predictive model.

Challenges we ran into

I had some trouble pinpointing what I wanted to focus my project on. I also had some difficulty creating the predictive model as it was my first time creating that. However, for both issues, I was able to troubleshoot, with the help of the internet and AI, and come to conclusions for both.

Accomplishments that we're proud of

I am proud that I was able to create a coherent project, as this is my first data science competition, and I am more of a beginner.

What we learned

I learned the importance of thoroughly understanding the code and what it does, so if I got some error in R, I could backtrack to figure out some way around it.

What's next for Understanding Seasonality of Deaths in Relation to Age Group

It could be interesting to further understand the relavance of deaths for the 65+ group for other diseases as well in terms of seasonality and location. This would allow that population to be aware of other factors when traveling to different state, especially during the winter.

Built With

• r
• tableau