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Z-Score Calculator

Z-Score
0
Percentile
50.00%
Probability (Area Left)
0.5000
Probability (Area Right)
0.5000
Show the math
Enter values to see the worked formula.

What Your Result Means

How This Calculator Works

You enter a raw score, the population mean, and the standard deviation. The tool computes z = (X − μ) / σ, then feeds that z into the standard normal cumulative distribution function (CDF) using the Horner-form error function approximation. The CDF gives the left-tail probability, and one minus that gives the right tail. Results assume the data follows a normal (Gaussian) distribution — for heavily skewed or small-sample data, interpret percentiles with caution.

Quick Questions

What z-scores are considered unusual?

In many fields, a z-score beyond ±1.96 (roughly the 2.5th or 97.5th percentile) is considered statistically unusual at the 5% significance level. Beyond ±2.58 corresponds to 1% significance.

Can I use this for sample data instead of a population?

If you're working with a sample mean and sample standard deviation, the result is technically a t-score, not a z-score. For large samples (n > 30), the difference is negligible; for smaller samples, use a t-distribution table instead.

What if my standard deviation is zero?

A standard deviation of zero means every value in the data set is identical, so the z-score is undefined (division by zero). The calculator will show "N/A" in that case.

How do I convert a z-score back to a raw score?

Use X = μ + z × σ. For example, if the mean is 100, the standard deviation is 15, and z is 1.5, the raw score is 100 + 1.5 × 15 = 122.5.

Is the percentile the same as a z-table lookup?

Yes. The percentile shown here is equivalent to looking up the cumulative probability in a standard normal (z) table. The calculator uses an error-function approximation accurate to about six decimal places.

Sources

Method & review

MethodologyHow we calculate this Reviewed & Updated2026-04 Next review2027-04

Estimate only. Results reflect your inputs and standard formulas. Double-check important decisions independently.