Z-Score Calculator

Calculate z-scores, percentiles, and areas under the standard normal curve. Free online z-score calculator.

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Results

Z-Score
1.5000
Percentile
93.32%
Area Below
0.9332
Interpretation:1.50σ above the mean — 93.3th percentile

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Z-Score Reference Table

Z-ScorePercentileInterpretation
-3.00.13%3.0 standard deviations below the mean
-2.50.62%2.5 standard deviations below the mean
-2.02.28%2.0 standard deviations below the mean
-1.56.68%1.5 standard deviations below the mean
-1.015.87%1.0 standard deviations below the mean
-0.530.85%0.5 standard deviations below the mean
+0.050.00%Exactly at the mean
+0.569.15%0.5 standard deviations above the mean
+1.084.13%1.0 standard deviations above the mean
+1.593.32%1.5 standard deviations above the mean
+2.097.72%2.0 standard deviations above the mean
+2.599.38%2.5 standard deviations above the mean
+3.099.87%3.0 standard deviations above the mean

Understanding Z-Scores & Normal Distribution

A z-score tells you how far a data point is from the mean in terms of standard deviations. It transforms any normal distribution into the standard normal distribution, where the mean is 0 and the standard deviation is 1. This makes it possible to compare values from completely different datasets.

The Empirical Rule (68-95-99.7)

In a normal distribution, approximately 68% of data falls within one standard deviation of the mean, 95% falls within two standard deviations, and 99.7% falls within three. This rule is why z-scores are so powerful: they immediately tell you how unusual a value is.

Practical Applications

  • Education: Standardized test scores (SAT, IQ) are often reported as z-scores or scaled from them.
  • Finance: Z-scores help measure how far a stock price deviates from its historical average.
  • Medicine:Growth charts use z-scores to compare a child's measurements to population norms.
  • Quality control: Manufacturing processes use z-scores to identify defects and outliers.

Frequently Asked Questions

A z-score (or standard score) measures how many standard deviations a data point is from the mean of a dataset. A z-score of 0 means the value is exactly average. Positive z-scores indicate values above the mean, while negative z-scores indicate values below the mean.

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