When would you use the median function on a dataset?

Using the median function on a dataset is particularly useful for identifying the value that falls in the middle once all values are arranged in order. This is especially advantageous when the dataset contains outliers or skewed distributions, as the median provides a better representation of the central tendency than the average. By calculating the median, you effectively pinpoint the value that divides the dataset into two equal halves—half of the numbers are below this value and half are above it.

Choosing the median is often preferable over the mean when the goal is to understand the typical value within a dataset while minimizing the impact of extreme values. This makes it a robust measure of central tendency, particularly in scenarios where data may not be symmetrically distributed.

In contrast, finding the average of values solely involves summing the data and dividing by the count, which can be skewed by outliers. The most frequent value, or mode, identifies what appears most often but does not reflect the center of the data. Calculating the total of all values produces a sum, which, while informative, does not offer insight into the distribution of individual values in relation to one another.