Compare Quartile Methods

Why Do Quartile Values Differ?

There is no single "correct" way to compute quartiles. Different statistical traditions, software packages, and textbooks use different conventions. The most common disagreement involves how to handle the median when splitting data into lower and upper halves for odd-count datasets. This tool lets you see all methods side-by-side so you can match your textbook or software.

Method 1: Exclusive (Median of Halves)

The most common method in North American textbooks and Casio calculators. For odd-count datasets, the median is excluded from both halves when computing Q1 and Q3.

Method 2: Inclusive

Used by some textbooks and TI calculators. For odd-count datasets, the median is included in both halves. This tends to produce Q1 values slightly closer to the median and Q3 values slightly closer to the median.

Method 3: Interpolation (Excel QUARTILE.INC)

Uses linear interpolation at positions 0.25(n−1) and 0.75(n−1). This is Excel's default QUARTILE and PERCENTILE function behavior. It can produce quartile values that are not actual data points.

Method 4: Excel QUARTILE.EXC

Uses positions 0.25(n+1) and 0.75(n+1). This is Excel's QUARTILE.EXC function. It requires at least 4 data points and can produce values outside the data range for very small datasets.

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