Air pollution control specialists in Southern California monitor the amount of ozone, carbon dioxide, and nitrogen dioxide in the air every hour. Hourly time series data exhibit seasonality, with contaminant levels showing patterns that vary across hours of the day. On July 15, 16, and 17, the following nitrogen dioxide levels were observed during the 12 hours from 6:00 a.m. to 6:00 p.m.

Use a multiple linear regression model with dummy variables as follows to develop an equation that accounts for seasonal effects in the data:

Time1 = 1 if the reading was taken between 6:00 am and 7:00 am; 0 otherwise

Time2 = 1 if the reading was performed between 7:00 am and 8:00 am; 0 otherwise

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Time11 = 1 if the reading was taken between 4:00 pm and 5:00 pm, 0 otherwise

Note that when the values of the 11 dummy variables are equal to 0, the observation corresponds to the time from 5:00 p.m. to 6:00 p.m.

If necessary, 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. (Example: -300)

Valor= 21,7 + 7,67 hora1+ 11,7 hora2+ 16,7 hora3+ 34,3 hora4+ 42,3 hora5+ 45,0 hora6+ 28,3 hora7+ 18,3 hora8+ 13,3 hora9+ 3,33 hora10+ 1,67 hora11

6:00 am - 7:00 am forecast	29.31
7:00 am - 8:00 am forecast	33.4
8:00 am - 9:00 am forecast	38.4
9:00 am - 10:00 am forecast	56
10:00 am - 11:00 am forecast	64
11:00 am - midday forecast	66.7
noon - 1:00 pm forecast	50
13:00 - 14:00 forecast	40
14:00 - 15:00 forecast	35
15:00 - 16:00 forecast	25.03
16:00 - 17:00 forecast	23.37
5:00 pm - 6:00 pm forecast	21.7

Let t = 1 to refer to the observation at hour 1 on July 15; t = 2 to refer to the observation at hour 2 on July 15; ...; and t = 36 to refer to the observation at the 12th hour of July 17. Using the dummy variables defined in part (b) and ts, develop an equation to account for seasonal effects and any linear trends in the time series.

If necessary, 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. (Example: -300)

Valor= 11,2 + 12,5 hora1+ 16,0 hora2+ 20,06 hora3+ 37,8 hora4+ 45,4 hora5+ 47,6 hora6+ 30,5 hora7+ 20,1 hora8+ 14,6 hora9+ 4,21 hora10+ 2,10 hora11+ 0.437 t

Based on the seasonal effects in the data and the linear trend estimated in part (d), calculate estimates of nitrogen dioxide levels for July 18.

6:00 am - 7:00 am forecast	40
7:00 am - 8:00 am forecast	44
8:00 am - 9:00 am forecast	49
9:00 am - 10:00 am forecast	66
10:00 am - 11:00 am forecast	75
11:00 am - midday forecast	77
noon - 1:00 pm forecast	60
13:00 - 14:00 forecast	51
14:00 - 15:00 forecast	45
15:00 - 16:00 forecast	36
16:00 - 17:00 forecast	34
5:00 pm - 6:00 pm forecast	32

This is the part I can't figure out, help me find the MSEs.

Is this model you developed in part (b) or the model you developed in part (d) more effective?

Model developed in part (b)	Model developed in part (d)
MSE