Refer to Exercise 14.66.

Data from Exercise 14.66

a. Use the simple linear regression model fit to the data to forecast the 2016 quarterly GDP. Place 95% prediction limits on the forecasts.
b. The GDP values given are seasonally adjusted, which means that an attempt to remove seasonality has been made prior to reporting the figures. Add quarterly dummy variables to the model. Use the partial F-test (discussed in Section 12.9) to determine whether the data indicate the significance of the seasonal component. Does the test support the assertion that the GDP figures are seasonally adjusted?
c. Use the seasonal model to forecast the 2016 quarterly GDP values.
d. Calculate the time series residuals for the seasonal model and use the Durbin-Watson test to determine whether the residuals are autocorrelated. Use α = .10.

GDP Year Year Quarter Quarter GDP 2011 2011 2011 2011 1 2 3 4 15,238.4 15,460.9 15,587.1 15,785.3 15,973.9 16,121.9 16,227.9 16,297.3 16,440.7 16,526.8 2013 2013 2014 2014 3 4 16,727.5 16,957.6 16,984.3 17,270.0 17,522.1 17,615.9 17,649.3 17,913.7 18,060.2 18,164.8 2 2012 2012 2012 2014 2014 2015 2015 2015 3 2 3 4 1. 2012 2013 2013 3 2015