A common way to communicate a high-level overview of a dataset is to find the values that split the data into four groups of equal size.

By doing this, we can then say whether a new datapoint falls in the first, second, third, or fourth quarter of the data.

The values that split the data into fourths are the *quartiles*.

Those values are called the first quartile (Q1), the second quartile (Q2), and the third quartile (Q3)

In the image above, Q1 is `10`

, Q2 is `13`

, and Q3 is `22`

. Those three values split the data into four groups that each contain five datapoints.

In this lesson, you will learn to calculate the quartiles by hand, and by using base R functions.

### Instructions

In this lesson we’ll be looking at a dataset about music. We’ve plotted a histogram of song lengths (measured in seconds) of 9,975 random songs.

Look up the length of a favorite song of yours. Do you think that song falls in the first, second, third or fourth quarter of the data?

For example, we’ve picked one of our favorite songs, *Chicago* by Sufjan Stevens. *Chicago* is `364`

seconds long — we’ve plotted it as a blue vertical line. It looks like *Chicago* is in either the third or fourth quarter of the data, but it’s hard to say for sure. Let’s find the quartiles of the dataset!

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