There is a set of variables related to miles per gallon (MPG) (outcome).
Here the difference of the MPG between automatic and manual transmissions is focused, the mtcars dataset in car package is taken as the data source, and techniques about regression models is used to solve the following two questions:
The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 10 aspects of automobile design
library(datasets)
mpgData <- with(mtcars, data.frame(mpg, am))
mpgData$am <- factor(mpgData$am, labels = c("Automatic", "Manual"))
#summary(mpgData)summary(mpgData[mpgData$am == "Automatic",])## mpg am
## Min. :10.40 Automatic:19
## 1st Qu.:14.95 Manual : 0
## Median :17.30
## Mean :17.15
## 3rd Qu.:19.20
## Max. :24.40summary(mpgData[mpgData$am == "Manual",])## mpg am
## Min. :15.00 Automatic: 0
## 1st Qu.:21.00 Manual :13
## Median :22.80
## Mean :24.39
## 3rd Qu.:30.40
## Max. :33.90fit <- lm(mpg ~ as.integer(am), data=mpgData)
summary(fit)##
## Call:
## lm(formula = mpg ~ as.integer(am), data = mpgData)
##
## 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) 9.902 2.628 3.768 0.000720 ***
## as.integer(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: 0.000285So, manual transmission is better than automatic for MPG, which increased by 7.2449393.
{r cache=TRUE boxplot(mpg ~ am, ylab = "miles per gallon (MPG)") plot(mpg ~ as.integer(am), xlab = "Automatic (1) or Manual(2)", ylab = "miles per gallon (MPG)") abline(fit, col=2) }) ## SourceCode part0_regmods-mtcars.Rmd