In [ ]:

    

library(MASS)
library(Boston)
library(ISLR)


    

In [ ]:

    

names(Boston)


    

In [ ]:

    

plot(medv ~ lstat, Boston)


    

In [ ]:

    

fit1 <- lm(medv ~ lstat, data = Boston)
fit1


    

In [ ]:

    

summary(fit1)


    

In [ ]:

    

plot(medv ~ lstat, Boston)
abline(fit1, col = "red")


    

In [ ]:

    

names(fit1)


    

In [ ]:

    

confint(fit1)


    

In [ ]:

    

predict(fit1, data.frame(lstat=c(5, 10, 15)), interval = "confidence")


    

In [ ]:

    

fit2 <- lm(medv ~ lstat+age, data = Boston)
summary(fit2)


    

In [ ]:

    

fit3 <- lm(medv ~ ., data = Boston)
summary(fit3)


    

In [ ]:

    

par(mfrow = c(2, 2))
plot(fit3)


    

In [ ]:

    

fit4 <- update(fit3, ~ . - age - indus)
summary(fit4)


    

In [ ]:

    

fit5 <- lm(medv ~ lstat*age, data = Boston)
summary(fit5)


    

In [ ]:

    

fit6 <- lm(medv ~ lstat + I(lstat^2), data = Boston)
summary(fit6)


    

In [ ]:

    

plot(medv ~ lstat)
points(lstat, fitted(fit6), col = "red", pch = 20, data = Boston)


    

In [ ]:

    

fit7 <- lm(medv ~ poly(lstat, 4), data = Boston)
summary(fit7)


    

In [ ]:

    

plot(medv ~ lstat, data = Boston)
points(Boston$lstat, fitted(fit6), col = "red", pch = 20)
points(Boston$lstat, fitted(fit7), col = "blue", pch = 20)


    

In [ ]:

    

plot(1:20, 1:20, pch = 1:20, cex = 2)


    

In [ ]:

    

library(ISLR)
names(Carseats)


    

In [ ]:

    

summary(Carseats)


    

In [ ]:

    

fit1 <- lm(Sales~. + Income:Advertising + Age:Price, data = Carseats)
summary(fit1)


    

In [ ]:

    

contrasts(Carseats$ShelveLoc)


    

In [ ]:

    

regplot <- function(x, y, ...) {
    fit1 <- lm(y ~ x)
    plot(x, y, ...)
    abline(fit1, col = "red")
}
regplot(Carseats$Price, Carseats$Sales, xlab = "Price", ylab = "Sales", col = "blue", pch = 20)