31. Air pollution control specialists in southern California monitor the amount of ozone, car- bon dioxide, and nitrogen dioxide in the air on an hourly basis. The hourly time series data exhibit seasonality, with the levels of pollutants showing patterns that vary over the hours in the day. On July 15, 16, and 17, the following levels of nitrogen dioxide were observed for the 12 hours from 6:00 A.M. to 6:00 P.M. file July 15: 25 28 35 50 60 60 40 35 30 25 25 20 July 16: 28 30 35 48 60 65 50 40 35 25 20 20 Pollution July 17: 35 42 45 70) 72 75 60 45 40 25 25 a. Construct a time series plot. What type of pattern exists in the data? b. Use the following dummy variables to develop an estimated regression equation to ac- count for the seasonal effects in the data. Hourl = 1 if the reading was made between 6:00 A.M. and 7:00 A.M.; 0 otherwise Hour2 = 1 if if the reading was made between 7:00 A.M. and 8:00 A.M.; 0 otherwise Hour11 = 1 if the reading was made between 4:00 P.M. and 5:00 P.M., 0 otherwise. Note that when the values of the 11 dummy variables are equal to 0, the observation cor- responds to the 5:00 P.M. to 6:00 P.M. hour. C. Using the estimated regression equation developed in part (a), compute estimates of the levels of nitrogen dioxide for July 18. d. Let t = 1 to refer to the observation in hour 1 on July 15; t = 2 to refer to the obser vation in hour 2 of July 15; . .. and t = 36 to refer to the observation in hour 12 of July 17. Using the dummy variables defined in part (b) and t, develop an estimated re- gression equation to account for seasonal effects and any linear trend in the time se- ries. Based upon the seasonal effects in the data and linear trend, compute estimates of the levels of nitrogen dioxide for July 18. 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