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Calculate Z-Score

Guide: Understanding Z-Scores

A z-score (or standard score) tells you how many standard deviations a value is above or below the mean of a distribution. The formula is: z = (x − μ) / σ

A z-score of +1.5 means the value is 1.5 standard deviations above the mean. A z-score of −2 means it is 2 standard deviations below the mean. Z-scores allow you to compare values from different distributions on a common scale.

The percentile tells you what percentage of the population scores at or below a given value. A z-score of 0 is the 50th percentile — exactly half the distribution is below it. A z-score of +1 is approximately the 84th percentile.

Example: if a student scores at the 92nd percentile on a standardised test, 92% of students scored at or below them.

Known Mean & SD: Use this when you know the population parameters — for example, IQ tests have a defined mean of 100 and SD of 15, or when your textbook provides the distribution parameters.

From raw data: Use this when you have a dataset and want to evaluate where a specific value sits relative to that data. The calculator will estimate the mean and SD from your data first.

Left tail P(X ≤ x): The probability that a randomly chosen value falls at or below your value. This is the same as the percentile expressed as a proportion.

Right tail P(X ≥ x): The probability that a randomly chosen value falls at or above your value.

Two-tailed P(|X| ≥ |z|): The probability of being this extreme in either direction. Used in hypothesis testing.

In a standard normal distribution:

  • |z| < 1.0: Within one SD of the mean — 68% of observations
  • |z| < 2.0: Within two SDs — 95% of observations
  • |z| < 3.0: Within three SDs — 99.7% of observations
  • |z| > 3.0: Very rare — only ~0.3% of a normal distribution

Values with |z| > 2.5–3 are commonly flagged as potential outliers.

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Normal Distribution Confidence Interval Descriptive Statistics T-Test Calculator