30. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. Quarter Year 1 Year 2 Year 3 1690 1800 1850 940 900 1 100 A WN 2625 2900 2930 2500 2360 2615 WEB Construct a time series plot. What type of pattern exists in the data? Use the following dummy variables to develop an estimated regression equation to ac- count for any seasonal effects in the data: Qtrl = 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 t, develop an estimated regression equation to account for seasonal effects and any linear trend in the time series. Based upon the seasonal effects in the data and linear trend, compute the quar- terly forecasts for next year. 31. Air pollution control specialists in southern California monitor the amount of ozone. car- socies data Economics 326 Assignment #4 Please use statistical software (Excel, for example) to estimate sample multiple regression line. For all problems, please write down the estimated sample regression lines in the standard format, and explain the meaning of coefficient of determination or R Square, as well as the meaning of each and all estimated coefficients (including the intercept) in the context of each problem and in plain English. Set #1 Page 705, problems 24 and 25 Set #2 Page 715, problems 35, 36, and 37 Set #3 Page 842, problems 30, 31