15 Overlaying plots

data("swiss")

str(swiss)

fertility = swiss$Fertility

Draw Histogram

data("swiss")
str(swiss)
fertility = swiss$Fertility
h = hist(fertility,
         probability = TRUE,
         ylim = c(0, 0.04),
         xlim = c(20, 110),
         breaks = 11,
         col = "#EFEFEF",
         border = 0,
         xlab = "Fertility",
         main = "Swiss Fertility Data\n 1888")

#Draw normal distribution curve

curve(dnorm(x, mean = mean(fertility), sd = sd(fertility)), col = "darkred", lwd = 3, add = TRUE)

#Kernel Density Plot ... follows the average

lines(density(fertility), col = "blue")
lines(density(fertility, adjust = 3), col = "green")

#A rug representation (1-d plot) of the data to the plot.

rug(fertility, col = "red")
x = 1:10
y1 = runif(10)
y2 = runif(10)
plot(x, y1, col = "steelblue", pch = 19, xlab = "X", ylab = "", ylim = c(0, 1))
points(x, y2, col = "red", pch = 19)
lines(x, y1, col = "steelblue")
lines(x, y2, col = "red")
legend(8, 1.0, c("Y1", "Y2"), col = c("steelblue", "red"), lty = c(1, 1))
x = 1:10
y1 = runif(10)
y2 = runif(10)
par(mfrow = c(1, 2))
plot(x, y1, col = "steelblue", pch = 19)
lines(x, y1, col = "steelblue")
plot(x, y2, col = "red", pch = 19)
lines(x, y2, col = "red")

For practice: