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Normal Distribution Calculator (Z-score & Percentile)

Convert a value to a z-score and percentile, or find probabilities under the bell curve — for any mean and SD.

Z-score
Percentile (P(X<x)) (%)
P(X > x) (%)

The z-score says how many standard deviations a value sits from the mean; the percentile converts that to 'what fraction scores below'. The empirical rule: ~68% of values fall within ±1σ, ~95% within ±2σ, ~99.7% within ±3σ. The default (x=130, μ=100, σ=15) is an IQ of 130 — the ~98th percentile.

Formula

z = (x - μ) / σ · percentile = Φ(z) (area left of z under the standard normal) · Φ via the error function
References: Standard normal distribution — any statistics text; Abramowitz & Stegun (1964), erf approximation

About Normal Distribution Calculator (Z-score & Percentile)

The normal distribution describes everything from test scores to measurement error to heights, and the z-score is how you locate any value within it: how many standard deviations it sits from the mean. This calculator converts a value (for any mean and SD) into its z-score and percentile, and gives the probability of scoring above or below it under the bell curve. It's the everyday tool for grading on a curve, interpreting standardized scores, setting quality-control limits, and understanding the empirical 68-95-99.7 rule that governs how data clusters around its average.

How to use Normal Distribution Calculator (Z-score & Percentile)

  1. 1Enter your values into Normal Distribution Calculator (Z-score & Percentile) — sensible, domain-typical defaults are pre-filled so you see a real result immediately.
  2. 2The result recomputes live using the formula shown on the page; there is no button to press.
  3. 3Adjust any input to compare scenarios, then read the worked example to see the substituted numbers.

Why use Normal Distribution Calculator (Z-score & Percentile)?

  • Computes Normal Distribution instantly in your browser — no sign-up, no upload, no server round-trip.
  • 100% free and unlimited, with the exact formula shown: z = (x - μ) / σ.
  • Runs entirely client-side, so every value you enter stays private on your device.
  • Live recompute as you type, with a worked example and authoritative references for trust.

Frequently asked questions

What is a z-score and why standardize?+

A z-score is (value - mean) / standard deviation — the number of SDs a value is from the mean. Standardizing puts any normal distribution onto one common scale, so a z of +2 means the same relative position whether you're measuring IQ, blood pressure or sales. It makes values from different distributions directly comparable and lets one table give all probabilities.

How do I get a percentile from a z-score?+

The percentile is the area under the standard normal curve to the left of the z-score — computed here via the error function. A z of 0 is the 50th percentile (the mean), z = +1 is ~84th, z = +2 is ~98th. This 'how many score below me' interpretation is what standardized tests report as your percentile rank.

What is the 68-95-99.7 rule?+

The empirical rule for normal data: about 68% of values fall within ±1 standard deviation of the mean, ~95% within ±2σ, and ~99.7% within ±3σ. It's a fast sanity check — a value beyond ±3σ is rare (under 0.3%) and often flagged as an outlier or out-of-control point in quality monitoring.

When does the normal distribution NOT apply?+

When data is skewed (incomes, wait times), bounded (proportions near 0 or 1), heavy-tailed (financial returns have more extremes than normal predicts), or multimodal. Applying z-scores to non-normal data gives misleading percentiles. Check a histogram or normality test first; for skewed data, consider transformations or distribution-specific methods.

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