CPM Homework Banner
12-13.
  1. Marissa wants to understand the possible effects of the weather on amusement park attendance, so she studies a linear association between the attendance at the amusement park and the temperature. Marissa makes the residual plot at right. Homework Help ✎

    1. Is a linear model appropriate? Why or why not?

    2. Marissa’s data follows. She has rounded attendance to the nearest hundred people. Make a scatterplot of the data. What kind of model might better represent Marissa’s data? Why?

      Temperature
      (˚F)

      71

      73

      78

      83

      91

      92

      73

      88

      95

      94

      checksum
      838

      Attendance
      (thousands)

      8.6

      13

      21.6

      25.9

      23.8

      25.9

      17.3

      25.9

      17.3

      21.6

      checksum
      200.9

    3. Fit a quadratic model to the data. What attendance does your model predict for a 95ºF day? Use appropriate precision.

The residual plot shows a clear U-shape. A curved regression model would have been better.

a = −0.083t² + 14.2t − 579, where a is the attendance (in 1000s of people) and t is the high temperature (ºF) that day. 20,900 people, rounded to the nearest 100 people.