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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

`.45,1.24,1.69`

, and . 66 . Furthermore, if we use a statistical software package to fit a straight line to the deseasonalized sales values, we find that the estimate of the trend is

`tI_(t)=22.61+.59t`

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,

`2.70,2.87,2.94`

, and 2.98 . (a) Calculate point predictions of bicycle sales in the four quarters of the next year. (Round yourd answers to

`2`

decimal places.) (b) Calculate approximate 95 precent prediction intervals for bicycle sales in the four quarters of the next year. ( Round your answers to 2 decimal places.)