If we use the multiplicative decomposition method to analyze the quarterly bicycle sales data given in Table 17.3 below, we find that the quarterly seasonal factors are .45, 126,173, and .68. Furthermore, if we use a statistical software package to t a straight line to the deseasonalized sales values, we find that the estimate of the trend is trt = 22.61 + .591': In addition, we find that the half-lengths of 95 percent prediction intervals for the deseasonalized sales values in the four quarters of the next year are, respectively, 2.72. 2.81, 2.96, and 3.06. \f(a) Calculate point predictions of bicycle sales in the four quarters of the next year. (Round your answers to 2 decimal places.) 6 Answer is complete but not entirely correct. Point Predictions = sn 8' tr t sn sn x tr 17 0.45 14.59 9 1a 1.26 39.88 6 19 1.73 56.48 9 20 0.68 20.99 9 (b) Calculate approximate 95 percent prediction intervals for bicycle sales in the four quarters of the next year. (Round your answers to 2 decimal places.) 9 Answer is complete but not entirely correct. 95% Prediction Intervals: y-hat17: 17.590 1 y-hat18: 42.650 1 y-hat19: 59_42 o ] V-hat20: 23.990 1