PROJECT Reducing Traffic Mortality in the USA How can we find a good strategy for reducing traffic-related deaths?

Project Description While the rate of fatal road accidents has been decreasing steadily since the 80s, the past ten years have seen a stagnation in this reduction. Coupled with the increase in number of miles driven in the nation, the total number of traffic related-fatalities has now reached a ten year high and is rapidly increasing.

By looking at the demographics of traffic accident victims for each US state, we find that there is a lot of variation between states. Now we want to understand if there are patterns in this variation in order to derive suggestions for a policy action plan. In particular, instead of implementing a costly nation-wide plan we want to focus on groups of states with similar profiles. How can we find such groups in a statistically sound way and communicate the result effectively?

Guided Project Make use of data wrangling, plotting, dimensionality reduction, and unsupervised clustering to identify groups of states with similar demographics of traffic accident victims.

Python Use Python to build a project that has a specific solution, with guided tasks and real-time automated code checks

R Use R to build a project that has a specific solution, with guided tasks and real-time automated code checks

Project Tasks

1. The raw data files and their format
2. Read in and get an overview of the data
3. Create a textual and a graphical summary of the data
4. Quantify the association of features and accidents
5. Fit a multivariate linear regression
6. Perform PCA on standardized data
7. Visualize the first two principal components
8. Find clusters of similar states in the data
9. KMeans to visualize clusters in the PCA scatter plot
10. Visualize the feature differences between the clusters
11. Compute the number of accidents within each cluster
12. Make a decision when there is no clear right choice