Exercise

# Q-Q plot

Another way to examine the normality of a distribution is with a Q-Q (quantile-quantile) plot. For this exercise, you will create a Q-Q plot for the country-level `Unemployment`

data you saw in the last exercise (available in your workspace as `countrydata`

). The Q-Q plot compares the theoretical quantiles expected under a normal distribution to the actual observed values (ordered). When a distribution is normally distributed, you will see a straight line. The more crooked the line is, the farther the distribution departs from normality. `pandas`

and `scipy.stats`

have been loaded into the workspace as `pd`

and `stats`

.

Instructions

**100 XP**

- Calculate the theoretical quantiles for a normal distribution.
- Create a DataFrame including your theoretical quantiles and the ordered values for
`Unemployment`

. - Create and print a Q-Q plot using your DataFrame.