Z-Score Calculator

What Is a Z-Score?

A z-score (also called a standard score) measures how many standard deviations a data point is from the mean of a distribution. A z-score of 0 means the value equals the mean. A z-score of 1.0 means the value is one standard deviation above the mean. A z-score of -2.0 means the value is two standard deviations below the mean.

The formula is: z = (X − μ) / σ where X is the data value, μ (mu) is the population mean, and σ (sigma) is the standard deviation.

Z-scores are used across statistics, finance, medicine, and education to compare values from different distributions, identify outliers, and find percentile ranks in a normal distribution.

How to Use This Z-Score Calculator

  1. Z-score from a value: Enter your data value, the mean, and standard deviation. The calculator finds the z-score and percentile rank.
  2. Percentile from z-score: Enter a z-score to find its percentile rank in the standard normal distribution.
  3. Value from z-score: Enter a z-score, mean, and standard deviation to find the raw data value at that position.

Z-Score Percentile Reference Table

Z-ScorePercentile% of Data Below
-3.00.13%0.13%
-2.02.28%2.28%
-1.56.68%6.68%
-1.015.87%15.87%
-0.530.85%30.85%
0.050.00%50.00%
0.569.15%69.15%
1.084.13%84.13%
1.593.32%93.32%
1.64595.00%95.00%
1.9697.50%97.50%
2.097.72%97.72%
2.57699.50%99.50%
3.099.87%99.87%

Worked Example: Test Score Percentile

A class exam has a mean of 72 and a standard deviation of 10. Sarah scored 88. What is her percentile?

Step 1: z = (88 − 72) / 10 = 16 / 10 = 1.6

Step 2: Look up z = 1.6 → approximately the 94.5th percentile

Sarah scored better than roughly 94.5% of the class. If there are 30 students, she placed in the top 1–2.

Common Z-Score Applications

  • Standardized testing (SAT, IQ): SAT scores are scaled to mean 1000, SD 200. IQ is scaled to mean 100, SD 15. Z-scores tell you exactly where you fall in the distribution.
  • Finance — Altman Z-Score: A model using z-scores from financial ratios to predict corporate bankruptcy risk. A score above 2.99 indicates low risk; below 1.81 indicates distress.
  • Outlier detection: Data points with |z| > 3 are typically flagged as outliers in datasets — they fall beyond 3 standard deviations.
  • Medical testing: Bone density T-scores and Z-scores compare patients to age-matched norms. A Z-score of -2.0 on bone density is considered below the expected range.
  • Quality control: Six Sigma manufacturing uses z-scores to measure process defect rates — a "6 sigma" process has a z-score of 6, meaning only 3.4 defects per million.

The Empirical Rule (68-95-99.7)

  • ±1σ (z = -1 to 1): Contains approximately 68.27% of data in a normal distribution
  • ±2σ (z = -2 to 2): Contains approximately 95.45% of data
  • ±3σ (z = -3 to 3): Contains approximately 99.73% of data
  • Only about 0.27% of data falls beyond ±3 standard deviations from the mean

Frequently Asked Questions About Z-Scores

What is a good z-score?

It depends on context. For test performance, a z-score of 1.0+ (top 84%) is strong. For quality control, you want z-scores close to 0 (near average). For outlier detection, |z| > 2 or 3 flags unusual values.

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 the value is 1.5 standard deviations below average — at approximately the 6.7th percentile.

What is a z-score of 1.96?

Z = 1.96 corresponds to the 97.5th percentile — meaning 97.5% of values in a normal distribution fall below this point. It's the standard critical value for 95% confidence intervals in two-tailed hypothesis tests.

How do I find a percentile from a z-score?

Look up the z-score in a standard normal table (z-table), or use the calculator above. The table gives the area under the normal curve to the left of the z-score, which equals the percentile rank.

What is a z-score of 2.0?

Z = 2.0 corresponds to the 97.72nd percentile — your value is 2 standard deviations above the mean and exceeds roughly 97.7% of the distribution.

Can z-scores be used for non-normal distributions?

Yes — you can calculate z-scores for any distribution. However, the percentile conversion using the normal distribution table is only accurate when the data is approximately normally distributed. For skewed distributions, use non-parametric methods.

What is the difference between a z-score and a t-score?

Z-scores use the known population standard deviation. T-scores are used when the population standard deviation is unknown and must be estimated from the sample — common in small samples. As sample size increases, t-distributions approach the normal distribution.

What IQ score corresponds to a z-score of 2?

IQ has mean 100 and SD 15. At z = 2: IQ = 100 + 2×15 = 130. This is in the "very superior" range, above 97.7% of the population.

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