Studying Firefighters' Job Title vs. Annual Salary
Collecting my Data:
Originally, I was going to base my data on the comparison of Apple to Samsung in yearly sales, but I couldn’t find enough accurate statistics to support my project. I knew I had to find something else to study, so I started looking at the City of Chicago Data Portal since I knew I would be able to collect an accurate set of data. I started browsing at categories and I found one called, “Current Employee Names, Salaries, and Position Titles”. Under that category, there were public service jobs such as Police, Firefighter, Street and Sanitation, etc. I chose to study the Firefighters because my Aunt used to be a Firefighter. The Firefighter data columns included Job Titles, Names, Department, Full or Part-Time, Salary or Hourly, and Annual Salary.
I made a scatter plot using 24 of the Job Titles and Annual Salary columns and then ranked them based on how I thought they should be ranked. I did this because it was very confusing to see all of the titles on the graph and not know what they meant. You see them as 1-11 instead of 1-24 because many titles appeared more than once. For reference, here are the titles and their ranks (1 is the highest and 11 is the lowest):
1. Captain - EMT (x1)
- $132,732
- $121,818
- $107,106 and $103,350
- $94,476 (x2)
- $99,324 (x2), $92,274, $89,148 (x2), and $84,870
- $97,386 (x2) and $93,666
- $68,616 and $56,304
- $91,080 (x2)
- $72,510, $68,616, and $56,304
- $107,106
- $105,804
My Graph:
I collected my data from the portal and put it into a spreadsheet. I then used the tools on Google Sheets to insert a graph of my data. I found the independent variable (x) to be the Job Titles (Rank) and the dependent variable (y) to be the Annual Salary. This means that the Firefighters’ Annual Salary depends on their Job Title (Rank). Looking at the graph, you can see that the Firefighters’ Annual Salary is, for the most part, between $50,000 and $100,000.
My Linear Equation:
On Google Sheets, I used my chart editor to find the equation of the linear trendline. As you can see from the graph, the equation is -3,862*x + 115,260. The slope is -3,862x, so that means as their Job Rank gets more insignificant, their Annual Salary gets lower.
My Prediction:
Based on my equation, I predicted that a random Firefighter-EMT would have a higher income (based on the fact that it’s farther than zero) than a random Paramedic in my dataset. To do this, I inputted 99,324, (random Firefighter-EMT) into my first equation and then 68,616, (random Paramedic) into my second equation. Here is what they look like: Equation 1) -3,862*99,324 + 115,260 = -383,474,028, Equation 2) -3,862*68,616 + 115,260 = -264,879,732. So you can see, a Firefighter-EMT would have a higher income than a Paramedic in this circumstance (because it’s farther than zero). I pinpointed those two points (99,324 and 68,616) on my graph to show that the EMT has a higher annual income than the Paramedic.
Final Observations:
An observation that I made is that the Firefighters in this dataset are pretty close in terms of how much they earn annually. Another thing I thought about was how these categories might look with other public service jobs such as Police or Streets and Sanitation. Overall, I think this data is useful because it allows you to see the correlation between a Firefighter’s Title and their Annual Salary.
An observation that I made is that the Firefighters in this dataset are pretty close in terms of how much they earn annually. Another thing I thought about was how these categories might look with other public service jobs such as Police or Streets and Sanitation. Overall, I think this data is useful because it allows you to see the correlation between a Firefighter’s Title and their Annual Salary.
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