The tutorial shows examples of how you can use built-in Probability Density Functions (PDF) in R, including PDF for normal distribution (dnorm), uniform distribution (dunif), and exponential distribution (dexp).

## Example 1: PDF for Normal Distribution

Normal distribution PDF `dnorm()`

in R returns the density of probability at 2. Note that it is standard normal distribution with mean = 0 and SD = 1.

> dnorm(2) [1] 0.05399097

We can see that 0.054 is the density of probability at point of 2. Visually, it is the value on Y-axis in the bell shape curve of normal distribution (see the figure below).

## Example 2: PDF for Uniform Distribution

Below, uniform distribution PDF `dunif()`

in R returns the density of probability at x=0 and x=1.5.

> dunif(1.5, min = -2, max = 2) [1] 0.25 > > dunif(0, min = -2, max = 2) [1] 0.25

As we can see above, both of them return 0.25. 0.25 is value on Y-asix corresponding with x=0 and x=1.5. To better understand that, we can plot the PDF function below to see them.

## Example 3: PDF for Exponential Distribution

In the following R code, exponential distribution PDF `dexp()`

in R returns the density of probability at x=1.

> dexp(1, rate=1) [1] 0.3678794

We can see the dexp(1, rate=1) returns 0.368. We can plot it below that 0.368 is the value on Y-asix corresonding with the x=1 for the exponential distribution PDF.