Z Score Calculator
Calculate Z-scores (standard scores) and percentiles. Determine how far a value is from the mean in standard deviations.
The data point to analyze
Population or sample mean
Population or sample standard deviation (cannot be zero)
What is a Z-score?
Z-score measures how many standard deviations a value is from the mean. Formula: Z = (X - μ) / rho�. Example: Test score 85, mean 70, SD 10 → Z = (85-70)/10 = 1.5. This score is 1.5 standard deviations above average. Positive = above mean, negative = below.
How do I interpret a Z-score?
Z=0: exactly average. Z=1: 1 SD above mean (~84th percentile). Z=2: 2 SD above (~98th percentile). Z=-1: 1 SD below (~16th percentile). Z>3 or Z<-3: very rare (outlier). About 68% of data falls between Z=-1 and Z=1 in normal distribution.
What is the difference between Z-score and percentile?
Z-score: distance from mean in standard deviations. Percentile: percentage of data below a value. They're related but different. Z=0 → 50th percentile. Z=1 → 84th percentile. Z=1.96 → 97.5th percentile. Z=2.58 → 99th percentile. Z-scores work for any distribution, percentiles for ranking.
When do I use Z-scores?
Comparing data from different scales (SAT vs ACT), identifying outliers (|Z|>3), standardizing data for analysis, calculating probabilities in normal distribution, quality control (Six Sigma), medical reference ranges, standardized test scoring.
What is a good Z-score?
Depends on context. For positive traits (IQ, test scores): Z>0 is above average, Z>2 is excellent. For negative traits (error rates, defects): Z<0 is good. In finance, Altman Z-score >2.99 indicates healthy company. Always consider what's being measured.