Final answer:
The claim that the median of a dataset is always an outlier is false. The median is a central value of a dataset, not necessarily an extreme value or outlier, and for symmetric distributions, it coincides with the mean and mode.
Step-by-step explanation:
The statement that the median of a dataset is always an outlier is false. The median is defined as the middle value of a dataset when it is ordered from least to greatest. In case of an even number of data values, the median is the average of the two middle values. The median is a measure of central tendency and does not necessarily reflect an outlier, which is a value significantly different from the rest of the data.
For a symmetric distribution, such as a bell-shaped normal distribution, the mean, median, and mode coincide at the same point. This, however, does not mean the median is an outlier but shows that for symmetric distributions, these measures of central tendency are equal.
Chebyshev's Rule is a statistical rule which states that a certain percentage of values lie within a certain number of standard deviations from the mean. This rule, however, is about the spread of the data and does not imply that the median is an outlier.