Which two methods are noted to ignore spikes in data?

• A. Naive forecast
• B. Cumulative mean and weighted mean
• C. Moving average
• D. Weighted mean alone

Answer: (B)

This question is about reducing the influence of spikes (outliers) when summarizing data with averages. The cumulative mean combines every observation up to the current point, so no single spike can dominate the statistic. As more data come in, the spike’s effect is diluted, and the mean stabilizes toward the overall level. The weighted mean takes that idea further by assigning different weights to observations; you can downweight unusual values or give less weight to older data, making the overall average less sensitive to a spike. In both cases, the method dampens the impact of abrupt, unusual observations, which is why they’re noted for ignoring spikes.