Z-Score Calculator
Convert a raw value to a z-score and find its percentile.
Results update as you type.
About this calculator
A z-score (standard score) tells you how many standard deviations a value lies above or below the mean: z = (x − μ) / σ. A positive z-score sits above the mean, a negative one below, and a z-score of zero is exactly at the mean. Standardising this way lets you compare values measured on completely different scales.
This calculator also returns the percentile — the probability that a value from a normal distribution is below x — and the right-tail probability, using the standard-normal cumulative distribution computed with an accurate error-function approximation, and it plots where x sits on the bell curve.
Worked example: if a test has a mean of 70 and a standard deviation of 10, a score of 85 gives z = (85 − 70) ÷ 10 = 1.5, meaning it is one and a half standard deviations above average. Under a normal distribution about 93.3% of scores fall below it, so it lands at roughly the 93rd percentile. Z-scores are the basis of standardised testing, quality control and the "68–95–99.7" rule.
Frequently asked questions
What does a z-score of 2 mean?
A z-score of 2 means the value is two standard deviations above the mean. Under a normal distribution about 97.7% of values fall below it, so it is a fairly extreme, high value.
Can a z-score be negative?
Yes. A negative z-score simply means the value is below the mean. A z-score of −1.5, for example, is one and a half standard deviations below the average.
How do I calculate a z-score?
Subtract the mean from your value and divide by the standard deviation: z = (x − μ) / σ. For x = 85, μ = 70 and σ = 10 the z-score is (85 − 70) ÷ 10 = 1.5.
How does a z-score relate to a percentile?
The z-score is converted to a percentile through the standard-normal cumulative distribution, which gives the proportion of values below it. A z-score of 0 is the 50th percentile, +1 is about the 84th and −1 about the 16th.
What is considered a high or unusual z-score?
By a common rule of thumb, z-scores beyond ±2 are unusual and beyond ±3 are rare, since about 95% of a normal distribution lies within two standard deviations of the mean and 99.7% within three.
Do I need a normal distribution to use a z-score?
You can standardise any value with the z formula regardless of shape, but the percentile and tail probabilities this tool reports assume the data follows a normal distribution. For strongly non-normal data those probabilities are only approximate.
API — use this calculator from code
Call this calculator as a free JSON endpoint — no key required. Send the field values below as query parameters or JSON. Read the full API docs →
Endpoint
GET https://calculator.free/api/v1/z-score/curl
curl "https://calculator.free/api/v1/z-score/?x=85&mean=70&sd=10"JavaScript fetch()
const r = await fetch(
"https://calculator.free/api/v1/z-score/?" + new URLSearchParams({
"x": "85",
"mean": "70",
"sd": "10"
}));
const data = await r.json();
console.log(data.results);Results are estimates for general guidance only, not financial, medical or tax advice.