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The third quartile, (Q_{3}) is \frac{3}{4} (or 75\% ) of the way through the data – the upper quartile. You can only find quartiles for quantitative (numerical) data sets, but they can be found for both discrete and continuous quantitative data sets.
The third quartile, Q3 is \cfrac{3}{4} \: ( or 75 \%) of the way through the data – the upper quartile. You can only find quartiles for quantitative (numerical) data sets, but they can be found for both discrete and continuous quantitative data sets.
5 wrz 2023 · The Corbettmaths Practice Questions on Quartiles and the Interquartile Range from a List.
The upper quartile (Q_3) is the value in the ordered data such that 75\% of the data is smaller than it and 25\% of the data is larger. In a data set size n , Q_3 is in position \dfrac{3(n+1)}{4} Q_2 denotes the median , found at \dfrac{n+1}{2}
Example: 5, 7, 4, 4, 6, 2, 8. Put them in order: 2, 4, 4, 5, 6, 7, 8. Cut the list into quarters: And the result is: Quartile 1 (Q1) = 4; Quartile 2 (Q2), which is also the Median, = 5; Quartile 3 (Q3) = 7
The upper quartile value is the median of the upper half of the data. The interquartile range is the difference between the upper and lower quartiles: \( IQR = Q_3 - Q_1 \). Outliers are the points lying beyond the upper boundary of \(Q_3 + 1.5 \times IQR\) and the lower boundary of \(Q_1 - 1.5 \times IQR\).
These worksheets provide a comprehensive and engaging way for students to practice calculating the first, second, and third quartiles, which are crucial in understanding data distribution and variability.
