What type of reference line is useful for evaluating forecast accuracy?

The most suitable reference line for evaluating forecast accuracy is the maximum and minimum lines. In the context of forecasting, these lines provide a frame of reference for understanding the spread and variability of the data points relative to the forecasted values.

By establishing maximum and minimum lines in a forecast graphic or chart, analysts can visualize the range within which actual results are expected to vary. This allows for a straightforward assessment of how tightly the forecast aligns with real-world outcomes. When actual data points fall outside these lines, it can signal potential inaccuracies in the forecast, enabling further investigation into the factors that may have influenced the deviation.

In contrast, the other options focus on different aspects of data interpretation. Average revenue lines would give a central tendency measure but do not provide insights into variability. Standard deviation lines show how much data typically deviates from the mean, which is useful but not as clear-cut for visual evaluation as maximum and minimum lines. Median revenue lines, while offering a middle point in revenue distribution, may not capture the extremes needed to evaluate forecast accuracy effectively. Thus, maximum and minimum lines stand out as the most effective tools for this specific purpose.