Practice: 1.5 x IQR Rule

Calculate the interquartile range (IQR) of the following data set: 10, 15, 20, 25, 30, 35, 40.

• 45

• 12

• 22

• 20

Tags

CCSS.6.SP.B.5C

Using the 1.5 x IQR rule, determine the lower fence for the data set with an IQR of 12.

• Lower fence = Q1 - 1.5 * IQR = Q1 - 1.5 * 12

• Lower fence = Q3 + 1.5 * IQR = Q3 + 1.5 * 12

• Lower fence = Q1 + 1.5 * IQR = Q1 + 1.5 * 12

• Lower fence = Q3 - 1.5 * IQR = Q3 - 1.5 * 12

If the lower quartile of a data set is 25 and the upper quartile is 45, what is the IQR?

• 20

• 40

• 15

• 30

Tags

CCSS.6.SP.B.5C

Apply the 1.5 x IQR rule to identify any outliers in the data set: 12, 15, 18, 20, 22, 25, 28, 30, 35, 40, 45, 50, 55, 60.

• Identify 55 as an outlier

• Identify 18 as an outlier

• Identify 30 as an outlier

• There are no outliers in the given data set.

What is the range of the data set: 5, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75?

• The range of the data set is 15.

• The range of the data set is 70.

• The range of the data set is 40.

• The range of the data set is 25.

Tags

CCSS.6.SP.B.4

CCSS.HSS.ID.A.1

Using the 1.5 x IQR rule, determine the upper fence for the data set with an IQR of 20.

• Upper Fence = Q3 - 1.5 * 20

• Upper Fence = Q1 + 1.5 * 20

• Upper Fence = Q3 + 20

• Upper Fence = Q3 + 1.5 * 20

If the lower quartile of a data set is 30 and the upper quartile is 50, what is the IQR?

• 20

• 60

• 40

• 10

Tags

CCSS.6.SP.B.5C

Apply the 1.5 x IQR rule to identify any outliers in the data set: 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, 48, 52, 56, 60, 64.

• There are no outliers in the given data set.

• Use the mean absolute deviation to detect outliers

• Exclude the highest and lowest values to find outliers

• Identify outliers using the 2 x IQR rule instead