The range of the sample data is 17.0 hurricanes. (Round to one decimal place as needed.) The standard deviation of the sample data is 6.2 hurricanes. (Round to one decimal place as needed.) The variance of the sample data is 38.9 hurricanes \( { }^{2} \). (Round to one decimal place as needed.) What important feature of the data is not revealed through the different measures of variation? A. The measures of variation reveal no information about the scale of the data. B. The measures of variation reveal nothing about how the numbers of hurricanes are spread. C. The measures of variation reveal nothing about the pattern over time. D. The measures of variation do not reveal the difference between the largest number of hurricanes and the smallest number of hurricanes in the data.

While measures of variation like range, standard deviation, and variance provide essential insights into the spread of data, they don't quite capture the underlying trends over time. Think of it like judging an entire movie based solely on a climactic scene—it misses the character development and plot twists that make the story rich. So, the answers lie not in the numbers but in the narrative of hurricane frequency and intensity across the seasons. Another fun fact is that if you look at historical hurricane data, you'll often find a cyclical pattern of activity. There are busy years and quieter years, influenced by various climatic conditions, such as El Niño or La Niña. Understanding this pattern gives meteorologists invaluable context on what the numbers reflect, helping them make predictions and prepare better for future hurricane seasons.