Which scenario best illustrates using adjacent feature attributes to compute a derived metric?

• A. Averaging visitor counts across parks
• B. Month-over-month change in website visits
• C. Filtering expired contracts
• D. Finding the nearest hospital

Answer: (B)

Deriving a metric from adjacent attributes means using values from neighboring data points to form a new measurement. In month-over-month change, you compare the website visits for the current month with the visits from the immediately preceding month. Those two values are adjacent in time, and their difference yields a derived metric that shows growth or decline between the two periods. This directly demonstrates using adjacent attributes to compute something new, rather than just aggregating or filtering data. The other scenarios don’t illustrate this as clearly: averaging across parks combines values across different features rather than adjacent ones, filtering is a straightforward selection, and finding the nearest hospital centers on spatial distance rather than a metric derived from adjacent attributes.