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Interquartile Range
Review

Nice work! You can now calculate the Interquartile Range of a dataset using R. The main takeaway of the IQR is that it is a statistic, like the range, that helps describe the spread of the center of the data.

However, unlike the range, the IQR is robust. A statistic is robust when outliers have little impact on it. For example, the IQRs of the two datasets below are identical, even though one has a massive outlier.

``````dataset_one = c(6, 9, 10, 45, 190, 200) # IQR is 144.5
dataset_two = c(6, 9, 10, 45, 190, 20000000) # IQR is 144.5``````

By looking at the IQR instead of the range, you can get a better sense of the spread of the middle of the data.

The interquartile range is displayed in a commonly-used graph — the box plot.

In a box plot, the ends of the box are Q1 and Q3. So the length of the box is the IQR.

### Instructions

We’ve set up a small `dataset` and are printing its range and IQR.

Try changing the maximum number in the dataset to different values.

What happens to the range when you make the maximum value `100000`? What happens to the IQR?

Try changing the minimum value to be more of an outlier as well.

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