The formal definition for the median of a dataset is:

*The value that, assuming the dataset is ordered from smallest to largest, falls in the middle. If there are an even number of values in a dataset, you either report both of the middle two values or their average.*

There are always two steps to finding the median of a dataset:

- Order the values in the dataset from smallest to largest
- Identify the number(s) that fall(s) in the middle

#### Example One: Even Number of Values

Say we have a dataset with the following ten numbers:

`$24,\ 16,\ 30,\ 10,\ 12,\ 28,\ 38,\ 2,\ 4,\ 36$`

The first step is to order these numbers from smallest to largest:

`$2,\ 4,\ 10,\ 12,\ [16,\ 24],\ 28,\ 30,\ 36,\ 38$`

Because this dataset has an even number of values, there are two medians: `16`

and `24`

— `16`

has four datapoints to the left, and `24`

has four datapoints to the right.

Although you can report both values as the median, people often average them. If you averaged `16`

and `24`

, you could report the median as `20`

.

#### Example Two: Odd Number of Values

If we added another value (say, `24`

) to the dataset and sorted it, we would have:

`$2,\ 4,\ 10,\ 12,\ 16,\ [24],\ 24,\ 28,\ 30,\ 36,\ 38$`

The new median is equal to `24`

, because there are 5 values to the left of it, and 5 values to the right of it.

### Instructions

**1.**

In the next two steps, you will manually sort an array, and then determine which value in the array is the median.

In **script.py**, we have an array with the ages of the first five authors from Le Monde’s survey:

`$29, 49, 42, 43, 32$`

Under `five_author_ages`

there is a variable called `sorted_author_ages`

. Change the `0`

s in `sorted_author_ages`

to the sorted values from `five_author_ages`

.

**2.**

Set `median_age`

equal to the median of the array.