To determine the best scale for representing the total snowfall on the y-axis, we first need to calculate the total amount of snowfall during the storm.
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First 2 hours: It snowed at a rate of 1 inch per hour. \[ 2 \text{ hours} \times 1 \text{ inch/hour} = 2 \text{ inches} \]
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Next 1.5 hours: It did not snow, so this contributes 0 inches.
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Next 3 hours: It snowed at a rate of 1.5 inches per hour. \[ 3 \text{ hours} \times 1.5 \text{ inches/hour} = 4.5 \text{ inches} \]
Now, we add the snowfall amounts together: \[ 2 \text{ inches} + 0 \text{ inches} + 4.5 \text{ inches} = 6.5 \text{ inches} \]
Given this total snowfall of 6.5 inches, the y-axis scale should be able to represent this amount effectively. Among the options provided (5, 2, 3, and 0.5), the best scale for the y-axis would be one that can accommodate at least 6.5 inches clearly.
The most appropriate choice from the options:
- 5: This would not reach 6.5 inches.
- 2: This would also not be sufficient.
- 3: This does not reach 6.5 inches.
- 0.5: This could allow for finer detail but would make reading at higher values cumbersome.
Thus, the best scale option that is more descriptive and can clearly show the total of 6.5 inches would need to be revised. However, if we stick strictly to provided values, none adequately fit.
So, while 0.5 may be the only one correctly listed but wouldn't ideally serve representation for the total yet, using a scale increment of 0.5 would allow for very exact marking even if overall inadequacy exists in highlighting the precise coverage due to limitations in the total height being visually apparent in graphical display. For a more effective representation in real-world scenarios, consider a scale of 1 inch per division is commonly usable for such totals (0-7 or 0-10), allowing a clearer overview, but approach via your choice would indicate, for the current set of data 0.5 would serve best fitting.
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