Z-Score Calculator
Calculate the z-score (standard score) and percentile rank for any value in a normal distribution. Convert raw scores to z-scores instantly.
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How to use this calculator
z measures how many standard deviations a value x is from the mean μ. Positive z means above average; negative means below.
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Enter the raw score (x), the population mean (μ), and the standard deviation (σ).
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The z-score tells you how many standard deviations the value is from the mean.
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The percentile shows what percentage of values fall below your score in a normal distribution.
Frequently asked questions
What is a good z-score?
In a normal distribution, 68% of values fall within z = ±1, 95% within z = ±2, and 99.7% within z = ±3. A z-score of 2 means the value is in the top 2.3%.
What is z-score used for?
Z-scores are used to standardise data from different scales, identify outliers, compare observations from different distributions, and calculate probabilities in hypothesis testing.
What if my data is not normally distributed?
Z-scores can still be calculated for any dataset, but the percentile interpretation only applies to normally distributed data. For non-normal data, use empirical percentile ranks instead.
Z-Score Calculator — Standard Score & Percentile
How to use the z-score
Use this z-score to he z-score (standard score) and percentile rank for any value in a normal distribution. Enter your values above and get your result in seconds. The tool is free, works on all devices, and keeps your data private — nothing is stored or shared.
How the z-score works
The z-score calculator uses standard formulas used in statistical analysis, data science, and research. Enter your inputs, and the tool calculates the result instantly in your browser. No server-side processing means your data stays on your device. Results update in real time as you change inputs.
Understanding z-scores in statistics
A z-score tells you how far a value is from the mean, measured in standard deviations. z = 0 means the value equals the mean. z = 1 means it is one standard deviation above. z = −2 means two standard deviations below. This standardisation lets you compare values from completely different scales.
Z-score and the normal distribution
In a perfectly normal distribution: 68.27% of values lie within z = ±1; 95.45% within z = ±2; 99.73% within z = ±3 (the empirical rule). The percentile from a z-score tells you what fraction of the population falls below that value.
Z-score: how it works
Statistical analysis underpins data science, research, quality control, and business intelligence. This tool applies established textbook formulas to your dataset and returns results instantly, eliminating manual calculation errors.
Who uses this tool?
Researchers, students, analysts, and business professionals use it to understand datasets quickly. Whether you are summarising survey responses or checking experiment results, this tool delivers the key figures instantly.
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Results are estimates for informational purposes only and do not constitute professional financial, medical, legal, or technical advice. Read full disclaimer →