Exercise

# Generating a single permutation

In the next few exercises, we will run a significance test using permutation testing. As discussed in the video, we want to see if there's any difference in the donations generated by the two designs - A and B. Suppose that you have been running both the versions for a few days and have generated 500 donations on A and 700 donations on B, stored in the variables `donations_A`

and `donations_B`

.

We first need to generate a null distribution for the difference in means. We will achieve this by generating multiple permutations of the dataset and calculating the difference in means for each case.

First, let's generate one permutation and calculate the difference in means for the permuted dataset.

Instructions

**100 XP**

- Concatenate the two arrays
`donations_A`

and`donations_B`

using`np.concatenate()`

and assign to`data`

. - Get a single permutation using
`np.random.permutation()`

and assign it to`perm`

. - Calculate the difference in the mean values of
`permuted_A`

and`permuted_B`

as`diff_in_means`

.