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Normal Distribution Calculator

Normal distribution calculator

Compute lower-tail, upper-tail, or interval probability for a normal distribution.

InputsStatistics5 fieldsLive

Result

0.8041735512

Interval probability P(-1.2 ≤ X ≤ 1.4).

Live update

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Advanced options
Flow
  • Enter mean and standard deviation.
  • Choose lower-tail, upper-tail, or interval mode.
  • Provide x or bounds and read resulting probability.
Example

Worked example: μ=0, σ=1, interval [-1.2, 1.4]

  1. 1 Compute z-values for both bounds.
  2. 2 Evaluate CDF at upper and lower bounds.
  3. 3 Probability = Φ(1.4) - Φ(-1.2) ≈ 0.8046

Interval probability is approximately 0.8046.

How
  1. Enter mean and standard deviation.
  2. Choose lower-tail, upper-tail, or interval mode.
  3. Provide x or bounds and read resulting probability.
Avoid
  • Using variance value directly instead of standard deviation.
  • Mixing up lower-tail and upper-tail interpretations.
  • Applying normal model to strongly skewed data without diagnostics.
Checks

Best fit

Normal Distribution Calculator is built for compute normal-distribution lower-tail, upper-tail, and interval probabilities. If Normal Distribution Calculator does not match the input scope, compare the answer with a second method.

Input check

Match the entered values to this rule before copying the answer: P(X≤x)=Φ((x-μ)/σ), P(a≤X≤b)=Φ((b-μ)/σ)-Φ((a-μ)/σ).

Sanity check

For Normal Distribution Calculator, use the worked example as a quick benchmark: Interval probability is approximately 0.8046. If the normal distribution calculator answer is far away, check whether an input, unit, or mode changed.

Before copying

Review this common issue first: using variance value directly instead of standard deviation.

FAQ
Can I use non-standard normal parameters?

Yes. Enter any mean and positive standard deviation.

What if standard deviation is zero?

The distribution becomes degenerate, so this tool requires positive standard deviation.

Is this exact or approximate?

CDF uses high-accuracy numerical approximation suitable for practical analysis.

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