Final answer:
To verify an outlier on a boxplot, calculate the fence values by finding the interquartile range (IQR) and applying the formula (Q1 - 1.5(IQR)) and (Q3 + 1.5(IQR)). Any data point that lies outside these boundaries is considered an outlier.
Step-by-step explanation:
To verify that the outlier shown on the boxplots for the female teenagers daily text messages is an outlier in that distribution, we need to calculate the fence values based on the given dataset. An outlier is any value that lies more than one and a half times the interquartile range (IQR) above the third quartile (Q3) or below the first quartile (Q1).
First, find the Q1 and Q3 of the dataset, and then calculate the IQR (Q3 - Q1). The fence values are determined by Q1 - 1.5(IQR) for the lower fence and Q3 + 1.5(IQR) for the upper fence. Any data point below the lower fence or above the upper fence is considered an outlier. Therefore, if the female teenager's number of daily text messages falls outside these fence values, it can be justified as an outlier.
Using the given data (for example, the provided boxplot data or a list of text message amounts), you would calculate these values and confirm whether the suspected outlier value indeed lies beyond the computed fences.