1 if Quarter 3, 0 otherwise. Quarterly forecasts for next year. 26. Textbook Sales. The quarterly...

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1 if Quarter 3, 0 otherwise. Quarterly forecasts for next year. 26. Textbook Sales. The quarterly sales data (number of copies sold) for a college text- book over the past three years follow. LO 4, 5, 6 Quarter 1234 Year 1 Year 2 Year 3 1690 1800 1850 $940 900 1100 2625 2500 2900 2930 2360 2615 a. Construct a time series plot. What type of pattern exists in the data? b. Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if == Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year. d. Let t = 1 to refer to the observation in Quarter 1 of Year 1; t = 2 to refer to the obser- vation in Quarter 2 of Year 1;...; and t = 12 to refer to the observation in Quarter 4 of Year 3. Using the dummy variables defined in part (b) and also using t, develop an equation to account for seasonal effects and any linear trend in the time series. Based the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year. upon 1 if Quarter 3, 0 otherwise. Quarterly forecasts for next year. 26. Textbook Sales. The quarterly sales data (number of copies sold) for a college text- book over the past three years follow. LO 4, 5, 6 Quarter 1234 Year 1 Year 2 Year 3 1690 1800 1850 $940 900 1100 2625 2500 2900 2930 2360 2615 a. Construct a time series plot. What type of pattern exists in the data? b. Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data. Qtr1 = 1 if Quarter 1, 0 otherwise; Qtr2 = 1 if == Quarter 2, 0 otherwise; Qtr3 = 1 if Quarter 3, 0 otherwise. c. Compute the quarterly forecasts for next year. d. Let t = 1 to refer to the observation in Quarter 1 of Year 1; t = 2 to refer to the obser- vation in Quarter 2 of Year 1;...; and t = 12 to refer to the observation in Quarter 4 of Year 3. Using the dummy variables defined in part (b) and also using t, develop an equation to account for seasonal effects and any linear trend in the time series. Based the seasonal effects in the data and linear trend, compute the quarterly forecasts for next year. upon