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The residual plot has the points following an upside down parabola. 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?





  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.