The following analysis looks into the affect of miles per gallon (MPG) based on type of transmission. We look at the mtcars dataset and compare the impact on MPG from a manual transmission versus an automatic one. By doing the analysis below, we find that on average a MANUAL transmission will give you a higher MPG rate.
library(datasets)
data("mtcars")
str(mtcars)
## 'data.frame': 32 obs. of 11 variables:
## $ mpg : num 21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
## $ cyl : num 6 6 4 6 8 6 8 4 4 6 ...
## $ disp: num 160 160 108 258 360 ...
## $ hp : num 110 110 93 110 175 105 245 62 95 123 ...
## $ drat: num 3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
## $ wt : num 2.62 2.88 2.32 3.21 3.44 ...
## $ qsec: num 16.5 17 18.6 19.4 17 ...
## $ vs : num 0 0 1 1 0 1 0 1 1 1 ...
## $ am : num 1 1 1 0 0 0 0 0 0 0 ...
## $ gear: num 4 4 4 3 3 3 3 4 4 4 ...
## $ carb: num 4 4 1 1 2 1 4 2 2 4 ...
head(mtcars)
## mpg cyl disp hp drat wt qsec vs am gear carb
## Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 0 1 4 4
## Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 0 1 4 4
## Datsun 710 22.8 4 108 93 3.85 2.320 18.61 1 1 4 1
## Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 1 0 3 1
## Hornet Sportabout 18.7 8 360 175 3.15 3.440 17.02 0 0 3 2
## Valiant 18.1 6 225 105 2.76 3.460 20.22 1 0 3 1
CR <- lm(mpg ~ am, data = mtcars)
summary(CR)
##
## Call:
## lm(formula = mpg ~ am, data = mtcars)
##
## Residuals:
## Min 1Q Median 3Q Max
## -9.3923 -3.0923 -0.2974 3.2439 9.5077
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 17.147 1.125 15.247 1.13e-15 ***
## am 7.245 1.764 4.106 0.000285 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 4.902 on 30 degrees of freedom
## Multiple R-squared: 0.3598, Adjusted R-squared: 0.3385
## F-statistic: 16.86 on 1 and 30 DF, p-value: 0.000285
We see that transmission is very significant in determining MPG. If you have an automatic transmission, your average MPG is 17.147 while a manual transmission your average is +7.245 more making it 24.392 MPG.
From the plot, we have further support that manual transmissions tend to have higher MPG’s.
Running a Poisson GLM did not result in a better fit. It is the same as with a standard linear model.
n <- length(mtcars$mpg)
e <- resid(CR)
yhat <- predict(CR)
max(abs(e -(mtcars$mpg - yhat)))
## [1] 4.840572e-14
max(abs(e - (mtcars$mpg - coef(CR)[1] - coef(CR)[2] * mtcars$am)))
## [1] 4.840572e-14
confint(CR)
## 2.5 % 97.5 %
## (Intercept) 14.85062 19.44411
## am 3.64151 10.84837
confint(glm1)
## Waiting for profiling to be done...
## 2.5 % 97.5 %
## (Intercept) 2.7312549 2.9484974
## mtcars$am 0.1976786 0.5070595
From this, we see that although the fit may not show a difference, the confidence of the Poisson GLM is greater than the standard linear model.