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A z-score tells how far a data value is from the mean, measured in standard deviations. This makes raw values easier to interpret because the number describes position within a distribution, not just size. Z-scores matter when two data sets use different units, scales, or spreads.

They help students compare test scores, measurements, and observations fairly.

Key Facts

  • z = (x - μ) / σ for a population value.
  • z = (x - x̄) / s for a sample value.
  • A positive z-score means the value is above the mean, and a negative z-score means it is below the mean.
  • A z-score of 0 means the value is exactly equal to the mean.
  • The absolute value |z| tells the distance from the mean in standard deviations.
  • For a normal distribution, about 68% of values are within z = -1 to z = 1, about 95% are within z = -2 to z = 2, and about 99.7% are within z = -3 to z = 3.

Vocabulary

Z-score
A standardized value that tells how many standard deviations a data point is from the mean.
Mean
The average value of a data set, found by adding all values and dividing by the number of values.
Standard deviation
A measure of how spread out data values are from the mean.
Standardization
The process of converting raw data values to a common scale so they can be compared.
Normal distribution
A symmetric bell-shaped distribution where values near the mean are most common.

Common Mistakes to Avoid

  • Using the raw score instead of x - μ in the numerator is wrong because a z-score measures distance from the mean, not the original value itself.
  • Forgetting the sign of the z-score is wrong because positive and negative values show whether the data point is above or below the mean.
  • Comparing raw values from different distributions is wrong when the means or standard deviations differ, because the same raw score can represent different relative positions.
  • Using variance instead of standard deviation in the formula is wrong because z-scores are measured in standard deviation units, not squared units.

Practice Questions

  1. 1 A quiz score is 84 in a class with mean μ = 76 and standard deviation σ = 4. Find the z-score and interpret it.
  2. 2 Student A scored 72 on a test with mean 60 and standard deviation 8. Student B scored 85 on a test with mean 78 and standard deviation 5. Which student performed better relative to their class?
  3. 3 Two data values have z-scores of -1.5 and 1.2. Explain which value is farther from its mean and what the signs tell you about their positions.