please show excel information step by step so i can understand how it is in done for future references.

Question 4: Find the "TextbookSales file. Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: qtr1 if quarter 1, 0 otherwise; qtr2 if quarter 2,0 otherwise; qtr3 if quarter 3, 0 otherwise. (Regression 1) Based on the model you developed, compute the quarterly forecasts for the next year. 1. What is the quarter 3 forecast? (Make sure no decimal places and no comma.) 2. What is the quarter 4 forecast? (Make sure no decimal places and no comma.) Let t = 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1; ...; and t = 12 refer to the observation in quarter 4 of year 3. Using the dummy variables defined in Regression 1 and t, develop an equation to account for seasonal effects and any linear trend in the time series. (Regression 2) Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for the next year. 3. What is the quarter 3 forecast? (Make sure no decimal places and no comma.) 4. What is the quarter 4 forecast? (Make sure no decimal places and no comma.) 5. Which regression model is more effective? (1 = Regression 1; 2 = Regression 2) . D B D E F 1 2 3 4 n 5 6 7 Year Quarter Sales 1 1 1690 1 2 940 1 3 2625 1 4 2500 2 1 1800 2 2 900 2 3 2900 2 4 2360 3 1 1850 3 2 1100 3 3 2930 3 4 2615 8 9 www WNNNN 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Question 4: Find the "TextbookSales file. Use a regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: qtr1 if quarter 1, 0 otherwise; qtr2 if quarter 2,0 otherwise; qtr3 if quarter 3, 0 otherwise. (Regression 1) Based on the model you developed, compute the quarterly forecasts for the next year. 1. What is the quarter 3 forecast? (Make sure no decimal places and no comma.) 2. What is the quarter 4 forecast? (Make sure no decimal places and no comma.) Let t = 1 refer to the observation in quarter 1 of year 1; t = 2 refer to the observation in quarter 2 of year 1; ...; and t = 12 refer to the observation in quarter 4 of year 3. Using the dummy variables defined in Regression 1 and t, develop an equation to account for seasonal effects and any linear trend in the time series. (Regression 2) Based upon the seasonal effects in the data and linear trend, compute the quarterly forecasts for the next year. 3. What is the quarter 3 forecast? (Make sure no decimal places and no comma.) 4. What is the quarter 4 forecast? (Make sure no decimal places and no comma.) 5. Which regression model is more effective? (1 = Regression 1; 2 = Regression 2) . D B D E F 1 2 3 4 n 5 6 7 Year Quarter Sales 1 1 1690 1 2 940 1 3 2625 1 4 2500 2 1 1800 2 2 900 2 3 2900 2 4 2360 3 1 1850 3 2 1100 3 3 2930 3 4 2615 8 9 www WNNNN 10 11 12 13 14 15 16 17 18 19 20 21 22 23