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Empirical Rule Worksheet

A Grade 9 math worksheet on the Empirical Rule (68-95-99.7 rule) for normally distributed data, including true/false, fill-in-the-blanks, and short answer questions.

Grade 9 Math Probability and StatisticsEmpirical Rule
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Includes

TextTrue / FalseFill in the BlanksShort Answer

Standards

CCSS.MATH.CONTENT.HSS.ID.A.4

Topics

mathgrade-9probabilitystatisticsempirical rulenormal distributionbell curve
6 sections · Free to use · Printable
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Empirical Rule Worksheet

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Read each question carefully and answer to the best of your ability. Show all your work for short answer questions.

The Empirical Rule, also known as the 68-95-99.7 rule, is a statistical rule which states that for a normal distribution, almost all data falls within three standard deviations of the mean.

- Approximately 68% of the data falls within one standard deviation of the mean.

- Approximately 95% of the data falls within two standard deviations of the mean.

- Approximately 99.7% of the data falls within three standard deviations of the mean.

μμ - σμ + σμ - 2σμ + 2σμ - 3σμ + 3σ68%95%99.7%

1. The Empirical Rule can be applied to any data distribution.

T

True

F

False

2. According to the Empirical Rule, approximately 95% of data falls within one standard deviation of the mean.

T

True

F

False

3. For a data set with a normal distribution, approximately   of the data will fall within three standard deviations of the mean.

4. The Empirical Rule is also known as the   rule.

5. If a data set is normally distributed, about 68% of the data lies between the mean minus one standard deviation and the mean   one standard deviation.

6. A set of test scores are normally distributed with a mean of 75 and a standard deviation of 5. What percentage of students scored between 70 and 80?

7. The heights of adult males in a certain city are normally distributed with a mean of 69 inches and a standard deviation of 3 inches. What range of heights would encompass approximately 95% of adult males?

8. Explain why the Empirical Rule is useful in statistics.