Air pollution control specialists in southern California monitor the amount of ozone, carbon dioxide, and nitrogen...

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Air pollution control specialists in southern California monitorthe amount of ozone, carbon dioxide, and nitrogen dioxide in theair on an hourly basis. The hourly time series data exhibitseasonality, with the levels of pollutants showing similar patternsover the hours in the day. On July 15,16 and 17, the observed levelof nitrogen dioxide in a city?s downtown area for the 12 hours from6:00 A.M. to 6:00 P.M. were as follows. 15-July 25, 28, 35, 50, 60,60, 40, 35, 30, 25, 25, 20 16-July 28, 30, 35, 48, 60, 65, 50, 40,35, 25, 20, 20 17-July 35, 42, 45, 70, 72, 75, 60, 45, 40, 25, 25,25 a. Construct a time series plot. What type of pattern exists inthe data? b. Use a multiple linear regression model with dummyvariables as follows to develop an equation to account for seasonaleffects in the data: Hour 1 = 1 if the reading was made between 6am and 7 am; 0 otherwise Hour 2 = 1 if the reading was made between7 am and 8 am; 0 otherwise Hour 3 = 1 if the reading was madebetween 8 am and 9 am; 0 otherwise Hour 4 = 1 if the reading wasmade between 9 am and 10 am; 0 otherwise continue this patternuntil Hour 11 = 1 if the reading was made between 4 pm and 5 pm' 0otherwise Note that when the values of the 11 dummy variables areequal to 0, the observation corresponds to the 5 pm to 6 pm hour.c. using the equation developed in part (b), compute estimates ofthe levels of nitrogen dioxide for July 18 d. Let t = 1 to refer tothe observation in hour 1 on July 15; t = 2 to refer to theobservation in hour 2 of July 15 ..., and t = 36 to refer to theobservation in hour 12 of July 17. using dummy variables devined inpart (b) and t, develop an equation to account for seasonal effectsand any linear trend in the time series. Based upon the seasonaleffects in the data and linear trend, compute estimates of thelevels of nitrogen dioxide for July 18 I only need the answer forpart D. This is my 3rd time submitting for the same answer.Thanks.

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