The third quartile, also known as the upper quartile or Q3, marks the 75th percentile of a dataset. It separates the highest 25% of values from the lowest 75%. In other words, three-quarters of the data fall at or below Q3, while the remaining quarter lies above it.
To find the third quartile:
- Sort the data in ascending order.
- Divide the dataset into four equal parts.
- The third quartile is the value that marks the boundary between the third and fourth quarters of the data.
If the dataset has an even number of values, Q3 is typically the median of the upper half of the data. If the number of values is odd, most methods exclude the overall median when identifying the upper half.
The third quartile is a key component of box plots, where it defines the top of the box. Analysts use the IQR and Q3 to detect potential outliers, which often lie far above Q3.
For example, in a dataset of housing prices, if the third quartile is $420,000, it means that 75% of the homes sold for $420,000 or less, and 25% sold for more.
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