Running head: MPG CASE STUDY
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MPG Case Study
Andrew D. Bessette
BQM 450 Statistical Techniques
May 11, 2014
Amedee Jacques
Southwestern College Professional Studies
MPG CASE STUDY
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MPG Hypothesis
How many times has a person or a couple gone to the automobile dealership with the
intention of purchasing reasonably priced high miles per gallon rated (MPG) vehicle? With the
prices of fuel topping out over four dollars a gallon, great gas mileage is a requirement.
Consumers tend to think that the large black numbers on a car's sales invoice which list the EPA
estimated fuel economy rating, as gospel. They believe that number is what they will get when
they are actually driving the vehicle. Unfortunately, in my experience, and what the statistical
data shows that this is usually untrue. What I discovered will show you the direct correlation
between the Environmental Protection Agency (EPA)/manufacturer estimated miles per gallon
(MPG) and the actual vehicle tested MPG. Initially I came into this “data finding” experiment
with a hypothesis that due to any amount of reasons, the EPA estimated fuel efficiency ratings
were grossly over the actual tested values. Once I completed my data collection, I found that
there was no conclusive evidence to support or contradict the hypothesis. Some of the car
manufacturers were right on the money with their estimates, some were close, and some were
way off. I chose to use two separate testing companies for this information. Edmunds is a vehicle
testing company with a very great reputation for honest reporting and impartial comparisons. The
EPA fueleconomy.gov website used their own specific testing procedures to obtain their data.
First thing that I need to cover is how the government agency EPA computes the estimated MPG
for each car, how that is different from real world driving. Overall the hypothesis stated would
be: Is the mean MPG of tested vs. actual equal to two or less? In Statistical terms would be as
follows: H 0 : =0 H a :  0 Basically this means that if there is any deviation from 0 MPG’s, then it
would be a rejection of the null hypothesis.
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How MPG is calculated
According to fueleconomy.gov, the government works very hard at calculating and
estimating the city and highway miles per gallon used. They take great care into the testing that
goes along with these numbers and stand by their results. The government posts all of this data
on a very user-friendly website called fueleconomy.gov. According to this site, testing begins
when “the vehicle's drive wheels are placed on a machine called a dynamometer that simulates
the driving environment—much like an exercise bike simulates cycling”. I for one had my
skepticism because in my experience an exercise bike did not take into account hills or wind
resistance, however the site assured me that wind resistance can be simulated by the amount of
resistance put on the wheels by the device, sort of like how you can increase the tension on the
exercise bike. Once on this machine a driver takes control and drives the car through an average
city and highway cycle. Stop and go, slow traffic, speed limits and alike are included in the
testing. For vehicles using carbon-based fuels (e.g., gasoline, diesel, natural gas, etc.), a hose is
connected to the tailpipe to collect the engine exhaust during the tests. While driving (according
to fueleconomy.gov) a hose connected to the exhaust collects and calculates the amount of fuel
that burns during the test. Apparently, this method is more accurate than using a fuel gauge.
However, it only works for vehicles that burn carbon based fuels, so electrics are out of the
question. In the city, the test starts with a cold engine and the operator drives the car in a manner
to replicate approximately 11 miles of rush hour stop-and-go traffic conditions. The vehicle top
speed is 56 mph with an average of 20 mph. For the highway drive test, the vehicle speed is an
average of 48 mph with a top speed of 60. Now at Edmunds.com their testing procedures are
quite a bit different. They test by actually driving the vehicles on a longer term. They sometimes
MPG CASE STUDY
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go many years test driving the same vehicle and reporting the data as it comes. Obviously, the
two testing methods are different; therefore, I expected that the data would be different. For
example, the top speed of the GOV testing was 60 mph on the highway, however many
highways have speed limits up to 75 mph now, so the outcomes of the “actual” vs. “tested”
mileage will be different. What were these differences, and how far off is the government agency
that posts those large black numbers on the window stickers?
Actual vs. Estimated
The EPA estimated mileage is just that, estimated. Nothing can take the place of actual
driving and getting on the spot data as Edmunds.com has done. The below table illustrates what
the estimated MPG for highway and city driving is, and the actual tested numbers.
Make/Model
Audi A6 Quattro 3.0T
Buick Regal 2.4 L
Cadillac ATS 2.5 L
Chevrolet Malibu 2.5L
Ford Focus SE
Mazda 3 i Grand Touring
Chrysler Pacifica
Mazda RX-8
Nissan Quest SL
Nissan Titan SE 4X4
Toyota Prius
Nissan Altima 3.5
Toyota Tundra 4X4
Nissan Rouge
Corvette Stingray
Volkswagen Beetle
Volkswagen Passat TDI
Porche 911 Carrera
Hundai Santa Fe
Est City
24
25
22
25
27
30
17
18
19
14
60
20
13
25
17
22
30
20
18
Actual
City
18
21
22
25
26
29
15.7
17.1
18
13.7
41.2
19
14.7
18.9
9.2
15.8
25.2
12.4
14.1
Est
Highway
38
36
33
36
37
41
22
24
26
18
51
26
17
32
29
25
40
28
24
Actual
Highway
27
30
33
36
36
40
20
22
22
18
54
27.5
16.6
26.9
30.8
32.6
44.4
31.4
25
Difference
City
6
4
0
0
1
1
1.3
0.9
1
0.3
18.8
1
-1.7
6.1
7.8
6.2
4.8
7.6
3.9
Difference
Highway
11
6
0
0
1
1
2
2
4
0
-3
-1.5
0.4
5.1
-1.8
-7.6
-4.4
-3.4
-1
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As you can see from the data there doesn’t seem to be any solid information that states that the
EPA vs. Tested numbers are better or worse as a whole, however there is quite a bit of difference
in the deviation from zero. The below chart shows the corresponding 19 vehicles and the data
obtained. The only direct correlation this graph depicts is that the two testing methods absolutely
yield different results.
Chart Title
70
60
50
40
30
20
10
0
-10
Est City
Actual City
Est Highway
Actual Highway
Difference City Difference Highway
-20
So what is the bottom line? This graph does show that the city and highways estimated miles
are different from the actual tested mileage. Is this due to the standardized testing from the EPA,
and the non-standardized driving of the actual driving conditions experienced? I will have to
answer that question at another time, but my hypothesis for that would be yes. The next chart
shows the differences for the corresponding 19 vehicles. Now is when the statistical
computations come in. I decided to figure out what the average differences for highway/city
actual vs. tested was. It would be much better for data collection if I did this. I could then see if
there was any statistical data that would show that city or highway deviations were more
significant. What I found was very surprising.
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25
Chart Title
20
15
10
5
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
-5
-10
Make/Model
Audi A6 Quattro 3.0T
Buick Regal 2.4 L
Cadillac ATS 2.5 L
Chevrolet Malibu 2.5L
Ford Focus SE
Mazda 3 i Grand
Touring
Chrysler Pacifica
Mazda RX-8
Nissan Quest SL
Nissan Titan SE 4X4
Toyota Prius
Nissan Altima 3.5
Toyota Tundra 4X4
Nissan Rouge
Corvette Stingray
Volkswagen Beetle
Volkswagen Passat TDI
Porche 911 Carrera
Hundai Santa Fe
Difference
City (X)
X- µ
(X - µ)²
Difference Hwy
X- µ
(X - µ)²
6
4
0
0
1
1
2.32
.32
-3.68
-3.68
-2.68
-2.68
5.3824
.1024
13.5424
13.5424
7.1824
11
6
0
0
1
1
10.48
5.48
-.516
-.516
.484
109.83
30.0304
.2662
.2662
.2342
.2342
1.3
0.9
1
0.3
18.8
1
-1.7
6.1
7.8
6.2
4.8
7.6
3.9
3.68
-2.38
-2.78
-2.68
-3.38
15.12
-2.68
-5.38
2.42
4.12
2.52
1.12
3.92
.22
5.6644
5.6644
7.1824
11.4244
228.6144
7.1824
28.9444
5.8564
16.9744
6.3504
1.2544
15.3664
.0484
387.4616
2
2
4
0
-3
-1.5
0.4
5.1
-1.8
-7.6
-4.4
-3.4
-1
.516
1.484
1.484
3.484
-.516
-3.516
-2.016
-.116
4.584
-2.316
-8.116
-4.916
-3.916
-1.516
7.1824
.484
2.2022
2.2022
12.1382
.2662
12.3622
4.0642
.0134
21.0130
5.3638
65.8694
24.1670
15.3350
2.2982
308.1562
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The following information on population variance and standard deviation was calculated and was
surprising to me.
Population Variance = 21.52 City. Standard Deviation City = 4.64
Population Variance = 17.119 Highway. Standard Deviation Highway = 4.14
The P value for both the city and highway data came out after a .01 significance level. This
turned out to be a df of 1. So since; H 0 : =0 H a :  0 does not equal 1. I have to reject the null
hypothesis. Even though there were some (as I saw it) significant differences in the tested vs.
actual data, the Population variance and standard deviations for both highway and city data was
not far off from each other. Therefore, it showed that the difference was not significantly more in
either of the categories. I would have thought that the city data would have had much more of a
significant deviation/variance due to the different driving situations that are faced every day.
Personally, I have experienced great city mileage compared to the sticker value due to being very
“light” on the pedal. Whereas, when I was constantly in a hurry, going the same distance, I used
much more fuel than I wanted to.
Summary
Whether or not you believe the stickers on the window of your new car is up to you.
According to my research, both the city MPG and Highway MPG deviations were nearly the
same. Unfortunately, my hypothesis was incorrect, but maybe not for the reasons that I thought. I
was under the impression that both the governmental Environmental Protection Agency testing
and the actual test-driving MPG ratings would be conducted in the same way. Therefore, bottom
line, is my data although interesting was inconclusive. If I wanted to find out whether the sticker
value was correct, I would need to re-create the EPA’s testing conditions in order to get more
conclusive and accurate data.
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References
EPA Estimated Fuel Efficiency Data, Vehicle Search data section., In Fuel Economy website.
Retrieved from http://www.fueleconomy.gov/
Car and Driver, Long term fuel economy data section. Car and Driver Website (2014).
Retrieved from http://www.caranddriver.com/comparisons/final-scoring-performance-data-andcomplete-specs-page-4-1