Standardize your data points with this easy-to-use calculator
How to Use This Calculator
Enter your raw score (the value you want to standardize)
Enter the mean (average) of your dataset
Enter the standard deviation of your dataset
Click "Calculate" to get your z-score
Interpret the result: positive z-scores are above the mean, negative are below
Options
Quick Examples
Calculator
Results
Normal Distribution
Standard Deviations from Mean
Frequently Asked Questions
What is a z-score?
A z-score measures how many standard deviations a data point is from the mean of a distribution. It standardizes different data points to make them comparable.
What does a z-score of -2 mean?
A z-score of -2 means the data point is 2 standard deviations below the mean of the distribution.
When should I use a z-score?
Z-scores are useful when you want to compare data points from different normal distributions, identify outliers, or calculate probabilities in a standard normal distribution.
What's considered a "significant" z-score?
Typically, z-scores beyond ±2 are considered unusual, and beyond ±3 are very unusual. However, significance depends on your specific context and requirements.
About Z-Scores
A z-score (standard score) represents how many standard deviations an element is from the mean.
Formula:
z = (x - μ) / σ
Where:
x = raw score
μ = population mean
σ = standard deviation
Quick Interpretation
z = 0: Exactly average
z > 0: Above average
z < 0: Below average
|z| > 2: Unusual
|z| > 3: Very unusual
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