Z-Score Calculator

Calculate z-score from a raw value, mean, and standard deviation.

Last updated: 2026-03-22

Results

Z-Score

0.5

Percentile

69.15%

P(Z ≤ z)0.6915
P(Z > z)0.3085
P(|Z| > |z|) two-tailed0.6171

A z-score of 0.5 means the value is 0.5 standard deviations above the mean.

What Is a Z-Score?

A z-score (also called a standard score) tells you how far a value is from the mean, measured in standard deviations. If a student scores 85 on a test where the class average is 80 and the standard deviation is 10, their z-score is 0.5 — meaning they scored half a standard deviation above average.

Z-scores let you compare values from different distributions. A z-score of 2.0 on one test means the same thing as a z-score of 2.0 on a completely different test — both are two standard deviations above their respective means.

The Formula

z = (x - μ) / σ

  • x = the raw value you want to standardize
  • μ = the mean (average) of the distribution
  • σ = the standard deviation of the distribution

Z-Scores and Percentiles

Every z-score maps to a percentile via the standard normal distribution. Some commonly used values:

Z-Score Percentile Meaning
-2.02.28%Far below average
-1.015.87%Below average
0.050.00%Exactly average
1.084.13%Above average
1.9697.50%Statistically significant (p < 0.05)
2.097.72%Far above average

Frequently Asked Questions

What is a z-score?

A z-score tells you how many standard deviations a value is from the mean. Positive means above, negative means below.

What does a negative z-score mean?

A negative z-score means the value is below the mean. A z-score of -1.5 means 1.5 standard deviations below average.

How do I find the z-score in Excel?

Use =STANDARDIZE(x, mean, standard_dev). For example: =STANDARDIZE(85, 80, 10) returns 0.5.

What z-score is statistically significant?

For a two-tailed test at the 0.05 significance level, z-scores beyond ±1.96 are statistically significant. For 0.01 level, the threshold is ±2.576.

Can z-scores be greater than 3?

Yes, but values beyond ±3 are rare in normally distributed data (only 0.3% of values). They may indicate outliers or non-normal distributions.

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