##### Statistical Analysis with R For Dummies An important aspect of base R graphics is the ability to add features to a graph after you create it. One way of showing histogram information is to think of the data as probabilities rather than frequencies. So instead of the frequency of a particular price range, you graph the probability that a car selected from the data is in that price range. To do this, you add

`probability = True`

to the arguments. Now the R code looks like this:

```> hist(Cars93\$Price, xlab="Price (x \$1,000)", xlim = c(0,70), main = "Prices of 93 Models of 1993 Cars",probability = TRUE)```

The result appears here. The y-axis measures Density — a concept related to probability. The graph is called a density plot.

The point of all this is what you do next. After you create the graph, you can use an additional function called `lines()` to add a line to the density plot:

```> lines(density(Cars93\$Price)) ``` The graph now looks like the following image.

So in base R graphics, you can create a graph and then start adding to it after you see what the initial graph looks like. It’s something like painting a picture of a lake and then adding mountains and trees as you see fit.