A snowstorm took place during the weekend. Meteorologists tracked the total amount of snowfall for the storm. For the first 2 hours, it snowed at a rate of 1 inch per hour. The snow stopped for an hour and a half, then resumed at a rate of 1.5 inches per hour for the next 3 hours. Based on this information, what scale would work best for representing the data on the y-axis?(1 point) Responses 3 3 5 5 2 2 0.5

1 answer

To determine the most suitable scale for representing the total snowfall on the y-axis, we first need to calculate the total snowfall from the snowstorm.

  1. First Period (2 hours):

    • Rate: 1 inch/hour
    • Snowfall: \(1 , \text{inch/hour} \times 2 , \text{hours} = 2 , \text{inches}\)
  2. Break (1.5 hours):

    • No snowfall during this period.
  3. Second Period (3 hours):

    • Rate: 1.5 inches/hour
    • Snowfall: \(1.5 , \text{inches/hour} \times 3 , \text{hours} = 4.5 , \text{inches}\)
  4. Total Snowfall:

    • Total = Snowfall from first period + Snowfall from second period
    • Total = \(2 , \text{inches} + 4.5 , \text{inches} = 6.5 , \text{inches}\)

Given that the maximum total snowfall is 6.5 inches, an appropriate scale for the y-axis should accommodate this value.

Looking at the response options provided:

  • 3
  • 5
  • 2
  • 0.5

Considering the total snowfall of 6.5 inches, none of these values seem to express an apt scale based on standard increments for data visualization. However, if we had to choose the best response option among them for a continuous scale leading up to 6.5 inches, we might select the smallest increment option, which is 0.5. This would allow for precise representation of the total snowfall measured in half-inch increments.

So the best scale for the y-axis is 0.5.