Z-Score Calculator

Z Score Calculator
Tip: decimals like 12.5 or 12,5 are accepted.
Enter values and press Calculate.

Z Score Calculator – Find Z Value & Standard Normal Probability

This free Z Score Calculator helps you quickly find the Z value (standard score) and the corresponding cumulative probability from the standard normal distribution. Enter a raw score, mean (μ), and standard deviation (σ) to instantly calculate how many standard deviations the value is from the mean.

What is a Z Score?

In statistics, a Z Score (or standard score) tells you how far a data point is from the mean, measured in standard deviations.

  • Z = 0 → the value is exactly the mean.

  • Z > 0 → the value is above the mean.

  • Z < 0 → the value is below the mean.

This makes Z scores essential for comparing values across different normal distributions.

Z Score Formula

The Z Score formula is:

$$ Z = \frac{X - \mu}{\sigma} $$

Where:

  • X = raw score (data point)
  • μ = mean of the population
  • σ = standard deviation

Example:

If a test score of 85 comes from a distribution with mean 70 and standard deviation 10:

$$ Z = \frac{85 - 70}{10} = \frac{15}{10} = 1.5 $$

This means the score is 1.5 standard deviations above the mean.

How to Use the Z Score Calculator

  • Enter your raw score (X).

  • Enter the mean (μ).

  • Enter the standard deviation (σ).

  • Click Calculate.

  • The calculator shows:

    • Z score

    • Φ(z) cumulative probability (area left of z)

    • Right-tail probability (area greater than z)

Z Distribution Table (Standard Normal)

Traditionally, Z scores are looked up in a Z table to find cumulative probabilities. The calculator eliminates the need for manual lookup by computing Φ(z) instantly using the normal distribution function.

  • Positive Z: gives the probability above the mean.
  • Negative Z: gives the probability below the mean.
  • Large Z values (±3): correspond to very small tail probabilities.

Worked Examples

  • Example 1 – Exam scores:
    X = 85, μ = 70, σ = 10
    → Z = 1.5, Φ(z) = 0.9332 (93.32% of scores are below 85).

  • Example 2 – Height data:
    X = 160 cm, μ = 170 cm, σ = 8
    → Z = -1.25, Φ(z) = 0.1056 (only 10.56% are shorter than 160 cm).

Applications of Z Scores

  • Education: comparing exam scores across subjects.

  • Research: standardising results across different datasets.

  • Finance: risk modelling and return normalisation.

  • Medicine: growth charts, diagnostic testing.

  • Quality control: identifying outliers and rare events.

FAQs

Q: What does a Z score of 2 mean?
A: The value is 2 standard deviations above the mean.

Q: What does a negative Z score mean?
A: The value is below the mean.

Q: What is a “high” Z score?
A: Usually, Z > 2 or Z < -2 indicates an unusual value.

Q: How do I convert Z to probability?
A: Use Φ(z), the cumulative distribution function. The calculator provides this automatically.

Q: What is the difference between Z score and percentile?
A: Percentile is the percentage of data below the value. A Z score can be converted into a percentile via the normal distribution.

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