WSU Commuting Times

As a second project for our class this week, we had to find out the average distance and time that commuter students attending Westfield State University traveled in one trip. Again, we could not use maps in our visualization of the data so below is the document that I've prepared for this assignment and then below that is the link to the website where I created the infograph! Check them out!

Click here to go to the website where I created the infograph and see my inforgaph in it's unedited format!

Enjoy and stay posted for more!

*UPDATE*

Hey everyone! I recently went through the data for the commuter students to figure out what the average straight-line distance is for commuter students to see if it would be different from the OD Cost Matrix tool that I ran to get the above information. As it turns out, there is quite a big difference. See, the OD Cost Matrix tool uses the network dataset, so the main streets for this project, to calculate how long it would take to get there but with a straight line distance, you are calculating it "as the crow flies" so you are not taking into account road distances. The average distance for commuter students using straight line distances is about 6.16 miles traveled for one trip to school. On the other hand, the average mileage traveled using the Cost Matrix was 15.6 miles. So you can see that there is a difference between the two tools. Neither tool is better than the other, you just need to keep in mind what you need to know from your data - maybe straight-line distance is a better choice for you or the cost matrix would be best - it all depends on your need!!

Fire Department Response Times

This week in class, we were asked to analyze the Fire Department response times for any city we want and see how the city would be affected if we removed one of the fire stations. Our challenge was to visualize our data without using a map. I chose Worcester, MA, as my city and removed the Tatnuk Square Fire Station (TSFS). I chose the TSFS because it was one of the outlier fire stations (located on the West side of the city) and I wanted to see a dramatic change in coverage. I analyzed the data from the US Census Bureau for population in the city along with the Network Analyst tool to determine how many people would be affected by the closing of the TSFS, mainly taking into account the critical 6 minute sudden cardiac arrest response time.

As stated in the document, one of the flaws with this analysis is that it does not take into account the surrounding cities' fire departments. The next town over's fire department may be able to respond to a victim with sudden cardiac arrest within 6 minutes, therefore reducing the impact of closing the TSFS. Another flaw with the analysis is that it assumes equal distribution of the population over each block group in the town. This is obviously not true; some block groups are very heavily populated on one end and very rural at the other end but this is the only way to fairly represent the block group.

*Block groups are clusters of census blocks created by the Census Bureau as a geographic level between blocks and census tracts. Block groups have anywhere from 600 to 3,000 people located within them and has the most detailed population data available.

Below is the document that I created for this project.

Also, you can click here to see the actual infograph on the web!

I hope you enjoy it and keep posted for more!