Interquartile Range Calculator

Real-Time Statistical Analysis & Outlier Detection Tool

Data Input & Configuration
You can enter up to 100 numeric values. Non-numeric values will be automatically filtered out.
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Data Visualization
Interquartile Range (IQR)
Data Range
Outliers

Understanding Interquartile Range (IQR)

The Interquartile Range (IQR) is a measure of statistical dispersion that represents the middle 50% of a dataset. It's calculated as the difference between the third quartile (Q3) and the first quartile (Q1). IQR is particularly useful for identifying outliers and understanding the spread of data around the median.

How to Use This Tool

  1. Enter your data - Input numbers separated by commas, spaces, or line breaks in the data input field.
  2. Adjust settings - Set decimal places for results and choose an outlier detection method.
  3. Calculate - Click "Calculate IQR" to instantly compute all statistics.
  4. Interpret results - Review the calculated quartiles, IQR, and identified outliers.
  5. Visualize - Examine the box plot to understand your data distribution at a glance.

Practical Applications of IQR

  • Outlier Detection: Values below Q1 - 1.5×IQR or above Q3 + 1.5×IQR are typically considered outliers.
  • Data Summary: IQR provides a robust summary of data spread that's not affected by extreme values.
  • Comparative Analysis: Compare variability between different datasets using their IQR values.
  • Data Cleaning: Identify and handle outliers before statistical analysis or modeling.
Tip: The IQR is more resistant to outliers than the range or standard deviation, making it ideal for skewed distributions or datasets with extreme values.
Statistical Results
Interquartile Range
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Data Points
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Q1 (25th %ile)
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Q3 (75th %ile)
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Median (Q2)
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Outliers
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Quartile Details
Quartile Value Position
Minimum -- --
Q1 (25%) -- --
Median (50%) -- --
Q3 (75%) -- --
Maximum -- --
Outlier Boundaries
Lower Bound
--
Upper Bound
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Data Points
0 data points
No data entered yet. Input data above to see points here.
Data Summary
Mean (Average) --
Standard Deviation --
Range --
Variance --