Using the 1.5×IQR Rule, all the box plots represent a data set that have a potential outlier.
What is the 1.5×IQR Rule?
This rule utilizes the quartiles and interquartile range (IQR) of a dataset to establish upper and lower fences, designating any data point outside these boundaries as an outlier; the upper fence is calculated as Q3 + 1.5(IQR), and the lower fence is calculated as Q1 - 1.5(IQR).
First box plot:
IQR = 40 - 25 = 15
Q3 + 1.5(IQR) = 40 + 1.5(15) = 62.5 [62.5 is beyond the threshold]
Q1 - 1.5(IQR) = 25 - 1.5(15) = 2.5
This box plot has a potential outlier.
Second box plot:
IQR = 35 - 20 = 15
Q3 + 1.5(IQR) = 35 + 1.5(15) = 57.5
Q1 - 1.5(IQR) = 20 - 1.5(15) = -2.5 [-2.5 is below the threshold]
This box plot has a potential outlier.
Third box plot:
IQR = 35 - 25 = 10
Q3 + 1.5(IQR) = 35 + 1.5(10) = 50
Q1 - 1.5(IQR) = 25 - 1.5(10) = 10 [10 is below the threshold]
This box plot has a potential outlier.
Fourth box plot:
IQR = 40 - 20 = 20
Q3 + 1.5(IQR) = 40 + 1.5(20) = 70 [70 is beyond the threshold]
Q1 - 1.5(IQR) = 40 - 1.5(20) = 10
This box plot has two potential outliers.
All the box plots have potential outlier.