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Data Analysis Project One
By: Logan Barnes, Edwin Edmondson, Sabrina Recendez and Yeu-Jen Lee
Submitted May 18th, 2023

Topic:
Electric Vehicle Ownership in the state of Washington

Points of interest:

  • What counties in Washington were most likely to have electric vehicles?
  • Are electric car owners in Washington more likely to own a pure electric vehicle or a hybrid electric vehicle?
  • Which brand and model of electric vehicle have the highest ownership in Washington?
  • What is the electric range of these make and models?
  • What is the income level of each county in Washington?
  • How does the level of income in each county affect their electric vehicle ownership?

Data Sources:
Our Findings:
  • King County is most likely to have electric vehicles.
  • Electric car owners in Washington is more likely to own a pure electric vehicle.
  • Tesla Model 3 is the most popular brand and model of electric vehicle in Washington.
  • The maximum electric range of BEV is 300 miles per charge, versus PHEV at 100 miles per tank of gas.
  • King County has the highest median income level in Washington, with the median income of $99,158 per household estimate (far exceeding other counties in the state).
  • There is a positively high correlation between electric vehicle ownership and median income in Washington.

Limitations:
  • Electric Range in our data were reported by the vehicle owners, which may be inaccurate.
  • Reporting errors in vehicle electric range can vary up to 36%, having access to manufacturer data would improve the accuracy of our BEV vs PHEV ranges.
  • Data only accounts for electric vehicle ownership in 2020, thus we are unable to analyze chronological patterns of electric vehicle ownership.
  • The data does not include reason for ownership, not having access to direct consumer data limits our ability to compare brand affinity to likelihood of ownership.
  • We did not compare ownership with EV charging stations, there is possibly a correlation between electric vehicle ownership and availability of charging stations.
  • We did not breakdown income further than county, which limits our insight into the cause of the income variation and resident spending habits.

Resources Used:

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