# solution

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Continue the analysis of the

(a) Obtain the residuals from the third-degree polynomial trend model in Exercise 13.57, part (c). Make a time series plot of the residuals and a lagged residual plot. Is there evidence of autocorrelation?

(b) Fit the attendance time series with two explanatory variables: lag one variable and t3. Report the fitted equation, the R2-value,

and the regression standard error s.

(c) Obtain the residuals from part (b). Make a time series plot of the residuals and a lagged residual plot. Do the plots suggest that

the lag-and-trend model is a good fit for the data series? Explain.

(d) Using the models from parts (a), (b), and (c) of the previous exercise, forecast average attendance per home game for the year

2008. Also, forecast year 2008 average attendance based on the fitted model from part (b) of this exercise.

(e) The actual average attendance per home game in 2008 was 40,743. Which of the four models provided the most accurate

forecast? Is this the same model you would have chosen based on R2-values and the regression standard errors?Chicago Cubs attendance time series.

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