Let's use `*norm`

as an example. From the documentation:

```
dnorm(x, mean = 0, sd = 1, log = FALSE)
pnorm(q, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
qnorm(p, mean = 0, sd = 1, lower.tail = TRUE, log.p = FALSE)
rnorm(n, mean = 0, sd = 1)
```

So if I wanted to know the value of a standard normal distribution at 0, I would do

```
dnorm(0)
```

Which gives us `0.3989423`

, a reasonable answer.

In the same way `pnorm(0)`

gives `.5`

. Again, this makes sense, because half of the distribution is to the left of 0.

`qnorm`

will essentially do the opposite of `pnorm`

. `qnorm(.5)`

gives `0`

.

Finally, there's the `rnorm`

function:

```
rnorm(10)
```

Will generate 10 samples from standard normal.

If you want to change the parameters of a given distribution, simply change them like so

`rnorm(10, mean=4, sd= 3)`