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(b) Use a multiple regression model with dummy variabies as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if uarter 1, 0 otherwise; Qtr2 = 1 if Quarter 2,0 otherwise; tr3-1 if Quarter 3 0 otherwise. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a sign before the blank. (Example: -300) Value 6.671Qtrit3 Qtr2t2Qtr3t (c) Compute the quarterly forecasts for next year based on the model you developed in part (b). If required, round your answers to three decimal places. 5.666 recast 3.66 4.666 6.66 orecast (d) Use multiple regression model to develop an equation to account for trend and seasonal effects in the data. Use the dummy variables you developed in part b) to capture seasonal effects and create a variable t such that t 1 for Quarter 1 in Year 1, t = 2 for Quarter 2 in Year 1, t = 12 for Quarter 4 in Year 3. If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there is a sign before the blank. (Example: -300) (e) Compute the quarterly forecasts for next year based on the model you developed in part (d). Round your interim computations and final answers to three decimal places 8.91 recast 6.91 7.916 9.91 (f) Is the model you developed in part (b) or the model you developed in part (d) more effective? If required, round your intermediate calculations and final answer to three decimal places. Model developed in part (b) Model developed in part (d) 1.222 0.28 0 Model developed in part (d) Justify your answer

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