PLEASE INCLUDE ALL EXCEL WORKING. SOLVER WORKING AND RECOMMNENDATIONS.

Arrow Air is a regional East Coast airline that has collected data for the percentage of available seats occupied on its flights for four quarters-(1) January March (2) April-June, (3) July- September, and (4) October-December-for the past 5 years. Arrow Air also has collected data for the average percentage fare discount for each of these quarters, as follows: Year 1 Quarter 1 2 3 4 1 3 3 4 1 2 3 4 1 2 3 4 1 2 3 Seat Occupancy (%) 63 75 76 58 59 62 81 76 65 70 78 69 59 61 83 71 60 66 86 74 Average Fare Discount (%) 21 34 18 26 18 40 25 30 23 28 30 35 20 35 26 30 25 37 25 30 Part (a) Develop a seasonally adjusted forecast model for seat occupancy. Forecast seat occupancy for year 6 by using a linear trend line forecast estimate for seat occupancy in year 6. Part (b) Develop linear regression models relating seat occupancy to discount fares in order to forecast seat occupancy for EACH QUARTER separately in year 6. Assume a fare discount of 20% for quarter 1, 36% for quarter 2, 25% for quarter 3, and 30% for quarter 4. Part (c) Compare the forecasts developed in (a) and (b) and indicate which one appears to be the best. Just an intuitive assessment would be enough. Part (d) Develop an adjusted exponential smoothing forecast model (alpha = 40 and beta = .40) for the quarterly data to forecast seat occupancy and compare its accuracy with the seasonally adjusted model developed in (a), using a forecast accuracy measure (e.g., MAD). Note that you must use the quarterly data (not aggregated annual data) and you can only estimate the seat occupancy for the first quarter of year 6. Bonus (5pts): Find the optimal value of alpha and beta in part (d) that minimizes the sum of squared errors