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Normal Distribution & Z-Scores

📊 Statistics
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Normal Distribution & Z-Scores

Interpret data using the bell curve and standardize with z-scores.

The normal distribution is a symmetric, bell-shaped probability distribution completely described by its mean Îŧ and standard deviation ΃. The empirical rule (68-95-99.7 rule) describes how data clusters around the mean.

The Empirical Rule

68% of data falls within Îŧ Âą ΃95% of data falls within Îŧ Âą 2΃99.7% of data falls within Îŧ Âą 3΃

Approximately symmetric — 34% on each side within one standard deviation.

z=x−Îŧ΃z = \frac{x - \mu}{\sigma}

A z-score measures how many standard deviations a data point lies above (positive) or below (negative) the mean. The standard normal distribution has mean 0 and standard deviation 1.

📊Computing a Z-Score
Exam scores are normally distributed with Îŧ = 75 and ΃ = 10. A student scored 92. z = (92 − 75)/10 = 1.7. This student scored 1.7 standard deviations above the mean.
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Remember This!

A z-score of 0 means the value equals the mean. Positive z: above the mean. Negative z: below the mean. Most real-world data falls between z = −3 and z = 3.

âœī¸ Try It!

Heights are normally distributed with Îŧ = 68 in and ΃ = 3 in. What is the z-score for a person who is 74 inches tall?

Take Quiz 📝 — 24 Questions