Deer car accident data from State Farm

We should teach with data sets representing ALL of our students. Why? You never know what example will stick in a student's head. One way to get information to stick in is by employing the self-reference effect

For example, students who grew up in the country might relate to examples that evoke rural life. Like getting the first day of buck season off from school and learning how to watch out for deer on the tree line when you are going 55 MPH on a rural highway.

Enter State Farm's data on the likelihood, per state, of a car accident claim due to collision with an animal (not specifically deer, but implicitly deer). Indeed, my home state of Pennsylvania is the #3 most likely place to hit a deer with your car.

State Farm shares its data per state:

https://www.statefarm.com/simple-insights/auto-and-vehicles/how-likely-are-you-to-have-an-animal-collision


I am also happy to share my version of the data, in which I turned all probability fractions (1 out of 522) into probability presented as a decimal (0.0019). 

You can use this data to discuss probability, calculate z-scores, differentiate between ordinal rank-ordering data and ratio percentage data, and discuss what happens when we change quantitative data into categorical data. 

This also opens up a conversation about data IRL. Insurance companies collect this data, which undoubtedly influences what we pay for auto insurance, the duration of hunting seasons, and why hunting a criticalant way to manage the state's deer herd.

FINALLY: I learned of this data from a CNN story, which is a secondary source of the data. However, I do love how CNN created a headline that is a great example of the availability heuristic


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