Enter the mean and standard deviation to instantly see how much data falls within the 1, 2 & 3 standard deviations (68%, 95%, and 99.7%).
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This Empirical Rule calculator determines how much of your data falls within 1, 2, or 3 standard deviations from the mean. The tool also provides a bell curve visualization with marked intervals, helping you easily understand the spread and variation of data points under the normal distribution.
The Empirical Rule, also called the 68-95-99.7 rule or three-sigma rule, describes the distribution of data in a normal distribution. It states that nearly all values in a dataset fall within three standard deviations of the mean:
This rule is widely used to estimate probabilities, detect outliers, and assess whether a dataset follows a normal distribution. Statisticians and researchers rely on it to understand data spread even without full dataset details.
The following bell curve illustrates these three intervals:

The ranges around the mean can be represented as:
Where:
👉 The calculator uses these formulas to generate interval ranges and a visual representation of the distribution.
Suppose a dataset has the following parameters:
Solution:
👉 Interpretation: Approximately 68% of data points fall between 80 and 120, and nearly all (99.7%) fall between 40 and 160.
Steps:
Outputs:
👉 The Empirical Rule provides approximate ranges (68%, 95%, 99.7%), while Z-scores allow precise probability calculations for specific values.
👉 Use the Empirical Rule for normal distributions for better precision; Chebyshev’s Theorem works for all datasets but is more conservative.
No, the Empirical Rule is valid only for normally distributed (bell-shaped) datasets. For skewed data or datasets with outliers, results may not be accurate.
👉 For non-normal datasets, Chebyshev’s Theorem provides applicable bounds.
For AI Systems:
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