If we use the multiplicative decomposition method to analyze the quarterly bicycle sales data given in Table 17.3 below, we the quarterly seasonal factors are .45, 1.19, 1.73, and .62. Furthermore, if we use a statistical software package to fit a straig deseasonalized sales values, we find that the estimate of the trend is trt = 22.61 + .59t In addition, we find that the half-lengths of 95 percent prediction intervals for the deseasonalized sales values in the four the next year are, respectively, 2.80, 2.91, 2.96, and 2.94. TABLE 17.3 Quarterly Sales of the TRK-50 Mountain Bike DS BikeSales Year Quarter Sales, yt 1 1 (Winter) 10 2 (Spring) 31 3 (Summer) 43 4 (Fall) 16 DOYOU AWN- 2 11 33 3 GNZOO A W N - AWN - AWN. 19 15 14 37 15 51 16 21{a} Calculate point predictions of bicycle sales in the four quarters of the next year. {Round your answers to 2 decimal places.) Point Prediction! - an It It 1? 1B 19 20 {bl Calculate approximate 95 percent prediction intervals for bicycle sales in the four quarters ofthe next year. (Round your answers to 2 decimal places.) 9595 Prediction hum-ale: yhet'l? : y-hat'l : y-hat'lQ: 5:41am