A small theater company has a linear regression model to estimate y = the concession stand sales in dollars, based on knowing x = the number of people in attendance.  The regression equation is:   = 6.72x + 11.50  and the correlation coefficient was r = 0.781.  The data set saw the number of people in attendance ranging from a minimum of 18 people to a maximum of 170 people.   Interpret the slope of the regression equation in the context of the problem. If it would make sense, interpret the y-intercept and if it doesn’t make sense to do that say why.           Predict the concession sales if there were 50 people in attendance. Then determine the residual for an observation in the data set where a play with 50 people in attendance had concession sales of $390.

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A small theater company has a linear regression model to estimate y = the concession stand sales in dollars, based on knowing x = the number of people in attendance.  The regression equation is:   = 6.72x + 11.50  and the correlation coefficient was r = 0.781.  The data set saw the number of people in attendance ranging from a minimum of 18 people to a maximum of 170 people.

 

  • Interpret the slope of the regression equation in the context of the problem. If it would make sense, interpret the y-intercept and if it doesn’t make sense to do that say why.

 

 

 

 

 

  • Predict the concession sales if there were 50 people in attendance. Then determine the residual for an observation in the data set where a play with 50 people in attendance had concession sales of $390.
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