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Z Score Calculator

Calculate Standard Score with Step-by-Step Derivation

Value (x)
Mean (μ)
Std Dev (σ)

Z Score Formula

z = (x - μ) / σ
Where: x = value, μ = population mean, σ = population standard deviation

Z-score standardizes any normal distribution to the standard normal distribution with μ=0 and σ=1.

σ must be positive. Z-score assumes data follows normal distribution.

What is Z Score?

The z-score (standard score) is a measure of how many standard deviations an element is from the mean. It allows comparison of scores from different normal distributions.

Positive Z

Value is above the mean

Negative Z

Value is below the mean

Z = 0

Value equals the mean

68-95-99.7 Rule

Percentages within ±1, ±2, ±3 σ

💡 Example: x=85, μ=75, σ=10. z=(85-75)/10=1. This means 85 is 1 standard deviation above the mean.

Applications

Statistics Standardization Comparisons Quality Control Testing

Frequently Asked Questions

What is z-score?
Z-score measures how many standard deviations a value is from the mean. z = (x - μ) / σ. Positive z means above mean, negative means below mean.
What does z-score tell us?
Z-score tells you how unusual a value is compared to the population. z=0 means average, z=1 means 1σ above mean, z=2 means 2σ above mean.
How to interpret z-score?
About 68% of data within z=±1, 95% within z=±2, 99.7% within z=±3. Values with |z|>3 are considered outliers.
When to use z-score?
Use z-score when population standard deviation is known and data follows normal distribution. For small samples with unknown σ, use t-score instead.

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