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Measures of Position Quartiles and Interquartile Range

Statistics • Numerical Descriptive Measures

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Measures of Position – Quartiles, Interquartile Range, Percentiles

Enter a set of ungrouped data (individual values). This tool ranks the data, finds the quartiles \(Q_1, Q_2, Q_3\), the interquartile range \(\text{IQR} = Q_3 - Q_1\), an optional percentile \(P_k\), and the percentile rank of a value \(x_r\). The diagrams show a bar cut into 4 equal parts (quartiles) and a 0–100% scale for percentiles.

Type the observations separated by commas, spaces, or line breaks. At least 4 numerical values are recommended.

Optional. Enter an integer \(1 \le k \le 99\) to approximate the percentile \(P_k\).

Optional. The percentile rank of \(x_r\) is the percentage of data values that are less than \(x_r\).

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Frequently Asked Questions

How does this calculator find Q1, Q2, and Q3 for ungrouped data?

It first ranks the data from smallest to largest. Q2 is the median of all values, then Q1 is the median of the lower half and Q3 is the median of the upper half, omitting the overall median from both halves when n is odd.

What is the interquartile range and how is it calculated?

The interquartile range measures the spread of the middle 50% of the data. It is calculated as IQR = Q3 - Q1.

How is the percentile Pk computed in this tool?

It uses an approximate ranked position: position = (k x n) / 100 in the ordered list. The position is rounded to the nearest whole number and the value at that rank is reported as Pk.

What is percentile rank for a value xr?

Percentile rank is the percentage of data values that are less than xr. It is computed as (number of values less than xr / n) x 100.

Why can quartiles or percentiles differ between textbooks or calculators?

Different sources use different rules for handling halves and positions, especially when n is odd or when the percentile position is not an integer. This calculator follows a specific ranking and rounding rule shown in the step-by-step explanation.