## The Inter-quartile Range

The inter-quartile range is a measure that indicates the extent to which the central 50% of values within the dataset are dispersed. It is based upon, and related to, the median.

In the same way that the median divides a dataset into two halves, it can be further divided into quarters by identifying the upper and lower quartiles. The lower quartile is found one quarter of the way along a dataset when the values have been arranged in order of magnitude; the upper quartile is found three quarters along the dataset. Therefore, the upper quartile lies half way between the median and the highest value in the dataset whilst the lower quartile lies halfway between the median and the lowest value in the dataset. The inter-quartile range is found by subtracting the lower quartile from the upper quartile.

For example, the examination marks for 20 students following a particular module are arranged in order of magnitude.

The median lies at the mid-point between the two central values (10th and 11th)

**= half-way between 60 and 62 = 61**

The lower quartile lies at the mid-point between the 5th and 6th values

**= half-way between 52 and 53 = 52.5**

The upper quartile lies at the mid-point between the 15th and 16th values

**= half-way between 70 and 71 = 70.5**

The inter-quartile range for this dataset is therefore **70.5 - 52.5 = 18** whereas the range is: **80 - 43 = 37.**

The inter-quartile range provides a clearer picture of the overall dataset by removing/ignoring the outlying values.

Like the range however, the inter-quartile range is a measure of dispersion that is based upon only two values from the dataset. Statistically, the standard deviation is a more powerful measure of dispersion because it takes into account every value in the dataset. The standard deviation is explored in the next section of this guide.