08-25-22
Procedure: For figure 1 I started by opening google spreadsheets and typing the data from the lab manual (listed below) into the spreadsheet in the same order it was given. Once it was all down I double clicked, and went to Insert and selected Chart. It automatically graphed the points I’d inserted with the weight of the SUV’s in pounds on the x-axis and gas mileage on the y-axis. I labeled the chart and found the Polynomial trendline worked best.
For figure 2 I used my calculator to invert the weight for the SUV’s by 1/weight. I then repeated the process of filling in the sheet as with figure 1 but with the digits for inverted weight. Inverted weight on the x-axis, gas mileage on the y-axis.
Data from lab manual:
SUV | Gas mileage mi/gal | WeightPounds |
Chevrolet Equinox | 25 | 3880 |
Chevrolet Tahoe | 19 | 5715 |
Dodge Durango | 20 | 5110 |
Ford Explorer | 22 | 4905 |
Honda CR-V | 29 | 3505 |
Hummer H3 | 20 | 4940 |
Jeep Commander | 19 | 5245 |
KIa sorento | 23 | 4310 |
Nissan Xterra | 23 | 4480 |
Toyota 4Runner | 22 | 4345 |
Volkswagen Tiguan | 28 | 3770 |
Figure 1: Gas Mileage vs. Weight with Polynomial trendline
The vehicles weight directly compared to their gas mileage
Figure 2: Gas Mileage vs. Inverse Weight with Exponential trendline 
Gas mileage compared to the inverse weight of the vehicles
INCORRECT GRAPH: The numbers for Weight and gas mileage were switched and put on the incorrect axis.
Discussion:
I found it crazy how closely correlated the weight of the vehicle and the gas mileage are.
The heavier the vehicle the more gas it needs to sustain it and this seems problematic for the environment. Perhaps if we could find ways to make lighter vehicles we could minimize gas output.