Firstly, let's see the simplest graph for R. With the following one-line R code, we draw a cosine function from -2π to 2π:
> plot(cos,-2*pi,2*pi)
The related graph is shown here:
Histograms could also help us understand the distribution of data points. The previous graph is a simple example of this. First, we generate a set of random numbers drawn from a standard normal distribution. For the purposes of illustration, the first line of set.seed() is actually redundant. Its existence would guarantee that all users would get the same set of random numbers if the same seed was used ( 333 in this case).
In other words, with the same set of input values, our histogram would look the same. In the next line, the rnorm(n) function draws n random numbers from a standard normal distribution. The last line then has the hist() function to generate...