Enter your dataset into the Data Set field (comma or space-separated numbers) and get back Q1 (25th percentile), Q2 median (50th percentile), Q3 (75th percentile), the Interquartile Range (IQR), plus the minimum, maximum, and range of your data — all calculated at once.
Q2 — Median (50th Percentile)
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Q1 — First Quartile (25th Percentile)
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Q3 — Third Quartile (75th Percentile)
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Interquartile Range (IQR)
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Minimum
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Maximum
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Range
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Count (n)
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Quartiles are three values that split a sorted dataset into four equal groups, each containing 25% of the data. Q1 is the 25th percentile, Q2 is the median (50th percentile), and Q3 is the 75th percentile. They help you understand the spread and distribution of your data at a glance.
First, sort your data in ascending order. Q2 (the median) divides the dataset in half. Q1 is the median of the lower half (excluding Q2 itself), and Q3 is the median of the upper half (excluding Q2). If the lower or upper half has an even number of values, Q1 or Q3 is the average of the two middle values in that half.
The Interquartile Range (IQR) is the difference between Q3 and Q1 (IQR = Q3 − Q1). It measures the spread of the middle 50% of your data and is a robust measure of variability because it is not affected by outliers or extreme values.
Sort the dataset in ascending order. If the number of values is odd, Q2 is the middle value. If the number of values is even, Q2 is the average of the two middle values. Q2 divides the entire dataset into equal lower and upper halves.
The range is simply the maximum value minus the minimum value, covering the full spread of the dataset. The interquartile range (IQR) measures only the middle 50% of the data (Q3 − Q1). The IQR is generally more useful because it is resistant to outliers, whereas the range can be heavily skewed by extreme values.
You can enter numbers separated by commas, spaces, tabs, or new lines. For example: '10, 20, 30, 40, 50' or '10 20 30 40 50'. You can also paste data directly from a spreadsheet. The calculator will ignore any non-numeric entries automatically.
Quartiles are widely used in statistics, finance, education, and data science. They form the basis of box plots, help identify outliers using the IQR method, describe income distributions, evaluate test score spreads, and summarize survey data. Any time you need to understand how data is distributed across four equal groups, quartiles are the right tool.
A common method is the IQR rule: calculate the lower fence (Q1 − 1.5 × IQR) and the upper fence (Q3 + 1.5 × IQR). Any data point below the lower fence or above the upper fence is considered a potential outlier. This method is used in box-and-whisker plots and is more robust than simply looking at the range.