Aft er a slight decrease following the 2007–2008 global fi nancial crisis, e-commerce sales in the United States have continued their strong growth for the past several years. Shown below are quarterly e-commerce sales fi gures released by the Census Bureau for the United States over a three-year period. Use these data to determine the equation of a trend line for e-commerce sales during this time and use the trend ‘model’ to forecast e-commerce sales for the third quarter of the year 2012. Year Quarter Sales ($ millions) 2008 1 36,244 2 36,691 3 36,180 4 33,393 2009 1 34,151 2 35,133 3 36,909 4 38,269 2010 1 39,159 2 40,472 3 42,381 4 44,517

The regression equation is Cost (1,000) = 1.57 +0.0407 Number of Passengers Predictor Constant Coef 1.5698 Number of Passengers 0.040702 SE Coef 0.3381 0.004312 T P 4.64 0.001 9.44 0.000 S = 0.177217 R-Sq 89.9% R-Sq (adj) = 88.9% Analysis of Variance. Source DF SS MS F P Regression 1 2.7980 2.7980 89.09 0.000 Residual Error 10 0.3141 0.0314 Total 11 3.1121 Number of Cost Obs. Passengers (1,000) Fit SE Fit Residual 123456789012 HH 61.0 4.2800 4.0526 0.0876 0.2274 63.0 4.0800 4.1340 0.0808 -0.0540 67.0 4.4200 4.2968 0.0683 0.1232 69.0 4.1700 4.3782 0.0629 -0.2082 70.0 4.4800 4.4189 0.0605 0.0611 74.0 4.3000 4.5817 0.0533 -0.2817 76.0 4.8200 4.6631 0.0516 0.1569 81.0 4.7000 4.8666 0.0533 -0.1666 86.0 5.1100 5.0701 0.0629 0.0399 10 91.0 5.1300 5.2736 0.0775 -0.1436 11 95.0 5.6400 5.4364 0.0912 0.2036 12 97.0 5.5600 5.5178 0.0984 0.0422