When evaluating data trends, which sorting method would help highlight increases and decreases effectively?

Sorting data in descending order is particularly effective for highlighting increases and decreases because it allows you to easily identify the highest values at the top of the list, making trends promptly visible. When trends must be assessed, for instance in sales data or financial reports, sorting from the highest to the lowest emphasizes the most significant gains and losses at a glance. This clarity helps stakeholders quickly grasp where performance is improving or declining.

In contrast, sorting data in ascending order would arrange the lowest values at the top, potentially obscuring significant increases in performance unless you scroll down through the data. A random order provides no inherent structure for evaluating changes, and an alphabetical order rearranges data based on letters, which does not provide insights into numerical trends. Thus, descending order is the most effective method when the goal is to evaluate data trends clearly and efficiently.