Case study analysis on ‘mtcars’ dataset.
Motor Trend Car Road Tests
Description:
The data was extracted from the 1974 Motor Trend US magazine, and comprises fuel consumption and 11 aspects of automobile design and performance for 32 automobiles (1973–74 models).
A data frame with 32 observations on 11 (numeric) variables.
[, 1] mpg Miles/(US) gallon
[, 2] cyl Number of cylinders
[, 3] disp Displacement (cu.in.)
[, 4] hp Gross horsepower
[, 5] drat Rear axle ratio
[, 6] wt Weight (1000 lbs)
[, 7] qsec 1/4 mile time
[, 8] vs Engine (0 = V-shaped, 1 = straight)
[, 9] am Transmission (0 = automatic, 1 = manual)
[,10] gear Number of forward gears
[,11] carb Number of carburetors
data=mtcars
View(data)
str(data)## '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 ... mpg <- mtcars$mpg
cyl <- mtcars$cyl
model1 <- lm(mpg ~ cyl)
model1##
## Call:
## lm(formula = mpg ~ cyl)
##
## Coefficients:
## (Intercept) cyl
## 37.885 -2.876 predict(model1, newdata=data.frame(cyl=8))## 1
## 14.87826 am <- mtcars$am
model2 <- lm(mpg~cyl+am)
model2##
## Call:
## lm(formula = mpg ~ cyl + am)
##
## Coefficients:
## (Intercept) cyl am
## 34.522 -2.501 2.567THE END