Exercise

# Normal distribution

On to the most recognizable and useful distribution of the bunch: the normal or *Gaussian* distribution. In the slides, we briefly touched on the bell-curve shape and how the normal distribution along with the central limit theorem **enables us to perform hypothesis tests.**

Similar to the previous exercises, here you'll start by simulating some data and examining the distribution, then dive a little deeper and examine the **probability of certain observations** taking place.

Instructions

**100 XP**

- Generate the data for the distribution by using the
`rvs()`

function with size set to 1000; assign it to the`data`

variable. - Display a
`matplotlib`

histogram; examine the shape of the distribution. - Given a standardized normal distribution, what is the probability of an observation greater than 2?
- Looking at
*our*sample, what is the probability of an observation greater than 2?