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Z Score to Percentile Calculator

Type or drag any z score and this z score to percentile calculator gives you its percentile rank instantly — the percentage of values that fall below it — with the shaded curve, the table method, and the landmarks worth memorising.

Or drag the slider z = 1.96

The slider starts at 1.96 — the most-used value in statistics: it marks the edge of the middle 95% of values.

Area to the left P(Z < z)share of values below your score—
Area to the right P(Z > z)share of values above your score—
Between mean and zbetween the average (z = 0) and your score—
Between −z and zthe middle slice — your score either side of the average—
Outside both tailsthe two far ends combined—
Percentileyou beat this % of values—
Show on the curve:
-3-2-1+0+1+2+3 mean = 0
For questions with two scores — the area between them:
Or drag both ends

Values generated from the standard normal cumulative distribution · Verified November 2026

z score to percentile calculator

How the conversion works

A percentile rank is just the cumulative probability wearing different clothes. The z table's cumulative value Φ(z) is the proportion of values below z; multiply it by 100 and you have the percentile. So the whole conversion is one lookup and one multiplication: percentile = Φ(z) × 100. A z score of 1.00 sits at Φ = 0.8413, the 84.13th percentile — it beats about 84% of the distribution. A z score of −0.67 sits at Φ = 0.2514, the 25.14th percentile — it beats only a quarter of values, which is exactly what a below-average score should say. The finder above reads out the percentile directly, alongside the raw proportions, so you can check one against the other.

Percentiles are the language results are reported in — test reports, growth charts, admissions statistics — while z scores are the language calculations are done in. Converting fluently between them is most of applied statistics: a percentile tells an audience where a result stands; the z score lets you keep computing with it. The full landmark set lives on the z score percentile chart, and the reverse journey is covered by the percentile to z score calculator.

Landmarks worth memorising

Worked conversion — exam score with z = 1.5

Φ(1.5) = 0.9332 from the positive z score table (row 1.5, column .00). Percentile = 0.9332 × 100 = 93.32nd percentile: the score stands higher than about 93% of candidates. In a cohort of 400, roughly 27 candidates scored higher. Notice what the percentile does NOT say: the score is not 93% correct, and it is not 43% better than average — percentiles are ranks, not amounts.

The mistakes this conversion attracts

Frequently asked questions

What percentile is a z score of 2?

Φ(2.00) = 0.9772, so z = 2 is the 97.72nd percentile — higher than about 97.7% of values, inside the top 2.3%. It is also the conventional "exceptional" line in many reporting systems.

Can a percentile be negative, or above 100?

No. Percentiles run from just above 0 to just below 100. Even the most extreme z scores stay inside: z = −3.99 is about the 0.003rd percentile and z = 3.99 about the 99.997th. If a calculation gives you a percentile outside 0–100, the wrong table layout was used.

What is the percentile for a z score of 0?

The 50th percentile, exactly. Half the distribution lies below the mean of a symmetric curve, which is why z = 0, the median and the 50th percentile are three names for the same point on the standard normal curve.

Is percentile the same as percentage?

No. A percentage measures how much of something you have (a test score of 85%); a percentile measures where you stand relative to others (the 85th percentile). The z score vs percentile page separates the ideas with examples, including why a weaker raw score can earn a higher percentile in a harder cohort.