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12-13.

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.

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

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

  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)

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    Attendance
    (thousands)

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

    , where a is the attendance (in s of people) and t is the high temperature (F) that day. people, rounded to the nearest people.