Exercise

# q-q plot

A **q-q plot** is a plot of the quantiles of one dataset against the quantiles of a second dataset. This is often used to understand if the data matches the standard statistical framework, or a normal distribution.

If the data is normally distributed, the points in the q-q plot follow a straight diagonal line. This is useful to check for normality at a glance but note that it is not an accurate statistical test. In the video, you saw how to create a q-q plot using the `qqnorm()`

function, and how to create a reference line for if the data were perfectly normally distributed with `qqline()`

:

```
> qqnorm(amazon_stocks,
main = "AMAZON return QQ-plot")
> qqline(amazon_stocks,
col = "red")
```

In the context of this course, the first dataset is Apple stock return and the second dataset is a standard normal distribution. In this exercise, you will check how Apple stock returns in `rtn`

deviate from a normal distribution.

Instructions

**100 XP**

- Draw a q-q plot for
`rtn`

titled "Apple return QQ-plot" - Add a reference line in red for the normal distribution using
`qqline()`