# The Standard Normal Distribution in R

Working with the standard normal distribution in R couldn’t be easier. The only change you make to the four norm functions is to not specify a mean and a standard deviation — the defaults are 0 and 1.

Here are some examples:

```> dnorm(0) ```
```[1] 0.3989423 ```
```> pnorm(0) ```
```[1] 0.5 ```
```> qnorm(c(.25,.50,.75)) ```
```[1] -0.6744898 0.0000000 0.6744898 ```
```> rnorm(5) ```
```[1] -0.4280188 -0.9085506 0.6746574 1.0728058 -1.2646055 ```
This also applies to the `tigerstats `functions:

```> pnormGC(c(-1,0),region="between") ```
`[1] 0.3413447`

```> qnormGC(.50, region = "below") ```
`[1] 0`

To standardize a set of scores so that you can compare them to other sets of scores, you convert each one to a z-score. The formula for converting a score to a z-score (also known as a standard score) is .