Air pollution control specialists in southern Califomia monitor the amount of ozone, carbon dioxide, and nitrogen diodde in the air on an hourly basis. The hourly 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 dia the 12 hours from 6:00 AM to 6:00 PM Click on the datafile logo to reference the data. DATA file July 15: 25 28 35 50 60 60 40 35 30 25 25 20 July 16: 28 30 35 48 60 65 SO 40 35 25 20 20 July 17: 35 42 45 20 72 75 60 45 40 25 25 25 (b) Use a multiple linear regression model with dummy variables as follows to develop an equation to account for seasonal effects in the data: Hourl = 1 If the reading was made between 6:00 A.M. and 7:00A.M.; 0 otherwise Hour2 = 1 If the reading was made between 7:00 A.M. and 8:00 A.M.; 0 otherwise Hour 11 = 1 If the reading was made between 4:00 P.M. and 5:00 P.M., o otherwise Note that when the values of the 11 dummy variables are equal to 0, the observation corresponds to the 5:00 P.M. to 6:00 P.M. hour. 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 round intermediate calculation. Level 21.7 + 7.67 Hourl + 11.7 Hour2 + 34.3 Hours + 42.3 Hours + 28.3 Hour 7 + 18.3 Hour 8+ 16.7 Hour3+ 3.33 Hourlo + 13.3 Hour + 1.67 Hourli (c) Using the equation developed in part (b), compute estimates of the levels of nitrogen dioxide for July 18, If required, round your answers to three decimal places. Do not round Intermediate calculation 6:00 a.m. - 7:00 a.m. forecast 7:00 a.m. - 8:00 a.m. forecast 8:00 a.m. - 9:00 a.m. forecast 9:00 a.m. - 10:00 a.m. forecast 10:00 a.m. - 11:00 a.m. forecast 11:00a.m. - noon forecast noon - 1:00 p.m. forecast 1:00 p.m. - 2:00 pm forecast 2:00 p.m. - 3:00p.m. forecast 3:00 pm - 4:00 pm forecast 4:00 pm - 5:00 pm forecast (d) Let t = 1 to refer to the observation in hour 1 on July 15; t = 2 to refer to the observation in hour 2 of July 15; ...; and t = Using the dummy variables defined in part (b) and t, develop an equation to account for seasonal effects and any linear tren If required, round your answers to three decimal places. For subtractive or negative numbers use a minus sign even if there Level = 11.2 + 12.5 Hourl + 16 Hour2 + 20.6 Hour3+ 37.8 Hour + 30.5 Hour 7 + 20.1 Hours + 14.6 Hourg + 4.21 Hour10 + 2.10 Hour11+ (e) Based on the seasonal effects in the data and linear trend estimated in part (d), compute estimates of the levels of nitrogen d If required, round your answers to three decimal places. Do not round intermediate calculation 6:00 a.m. - 7:00 a.m. forecast 7:00 a.m. - 8:00 a.m. forecast 8:00 a.m. - 9:00 a.m. forecast 9:00 a.m. - 10:00 a.m. forecast 10:00 am - 11:00 a.m. forecast 11:00 a.m. noon forecast noon - 1:00 p.m. forecast 1:00p.m. 2:00 p.m. forecast 2:00 p.m. - 3:00 p.m. forecast 3:00p.m - 4:00 pm, forecast 4:00 pm - 5:00 p.m. forecast 5:00 p.m. - 6:00 p.m. forecast (e) Based on the seasonal effects in the data and linear trend estimated in part (d), compute estimates of the levels of nitrogen dioxi If required, round your answers to three decimal places. Do not round intermediate calculation 6:00 a.m. - 7:00 a.m. forecast 7:00 a.m. - 8:00 a.m. forecast 9:00 a.m. - 9:00 a.m. forecast 9:00 a.m. - 10:00 a.m. forecast 10:00 a.m. - 11:00 a.m. forecast 11:00 a.m. - noon forecast noon - 1:00 pm, forecast 1:00 p.m. - 2:00 pm, forecast 2:00 p.m. - 3:00 p.m. forecast 3:00 p.m. - 4:00 pm, forecast 4:00 p.m.. 5:00 p.m. forecast 5:00 pm - 6:00 pm, forecast (1) Calculate the MSE for the regression models developed in parts (b) and (d). If required, round your answers to three decimal places. Model developed in part (b) Model developed in part (d) MSE is the model you developed in part (b) or the model you developed in part (c) more effective? The model developed in - Select your answer is more effective because it has the - Select your answer - MSE