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library(ISLR)


    

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# (a)


    

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pairs(Auto)


    

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summary(Auto)


    

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names(Auto)


    

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cor(subset(Auto, select = -name))


    

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# (c)
# i. From the following, there is a relation
# ii. It's suprising cylinders have no significant relation, but this is because
#     weight presents
# iii. newer cars have better efficiency
fit <- lm(mpg ~ .-name, data = Auto)
summary(fit)


    

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fit2 <- lm(mpg ~ cylinders, data = Auto)
summary(fit2)


    

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# (d)
par(mfrow = c(2,2))
plot(fit)


    

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# (e)
fit <- lm(mpg ~ cylinders*displacement+displacement*weight, data = Auto)
summary(fit)


    

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# lm.fit3 <- lm(mpg~log(weight)+sqrt(horsepower)+poly(acceleration, 2), data = Auto)
lm.fit3 = lm(mpg~log(weight)+sqrt(horsepower)+acceleration+I(acceleration^2), data = Auto)
summary(lm.fit3)


    

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lm.fit3 = lm(mpg~acceleration+I(acceleration^2), data = Auto)
#lm.fit3 = lm(mpg~poly(acceleration, 3), data = Auto)
summary(lm.fit3)