In Statistics, Quartile Deviation is a measure of dispersion that tells us how spread out the middle 50% of our data is. It is also known as the Semi-Interquartile Range.
The concept of quartiles divides a ranked dataset into four equal parts. Q2 is the Second Quartile, which is exactly the same as the Median (the exact middle of the data).
Quartile Deviation (QD) = (Q₃ - Q₁) / 2
Where:
(Note: The difference between Q₃ and Q₁ is called the Interquartile Range (IQR). Quartile Deviation is simply half of the IQR).
To compare the dispersion of two different datasets, we use the relative measure called the Coefficient of Quartile Deviation.
Coefficient of QD = (Q₃ - Q₁) / (Q₃ + Q₁)
Unlike the 'Range' (Highest - Lowest value) which is highly affected by extreme outliers, the Quartile Deviation only looks at the middle 50% of the data. This makes it a much more robust and reliable measure of spread when your data has extreme high or low values (outliers).
QD = (Q₃ - Q₁) / 2 QD = (50 - 30) / 2 = 20 / 2 = **10**.
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