Question

How do you identify outliers when displaying data in a box plot?

Answer 1

Hint: To get the answer for this question it is required to know the outliers. We should determine the occurrence of the Outliers from the given data. Then we can take the point beyond an inner fence on either side which is considered a mild outlier. From this we can identify the outliers from the box plot.

Complete step-by-step answer:
An outlier is an observation that lies an abnormal distance from other values in a random sample from a population. Two graphical techniques for identifying outliers: scatter plots and box plots.
A point beyond an inner fence on either side is considered a mild outlier. A point beyond an outer fence is considered an extreme outlier.
We know that the Outliers occur when outside the range of \[{{Q}_{1}}-1.5(IQR)\] and \[{{Q}_{3}}+1.5(IQR)\]
Here we know that IQR means Inter quartile range, or the third quartile minus the first quartile.
\[{{Q}_{1}}\] is the first quartile and \[{{Q}_{3}}\] is the third quartile.
If an outlier occurs, it is graphed on the box-and-whisker plot as a dot. But when the box-and-whisker plot is displayed we can identify Outliers using the ranges mentioned.

Note: It is necessary that we know what are outliers to determine them from the displaying data given in the box plot. The student should know about the range limits outside which the Outliers will occur to identify them.