As a manager of a regional airport you need to forecast monthly passenger flow (number of passengers flying in and out) through the airport for planning and budgeting purposes. You have historical monthly airport passenger data over last five years - ending in December, 2021 (download EXCEL file Airport_Passenger_data.xlsx from Canvas). You want to explore the idea of exponential smoothing to model the history and prepare a forecast for the following year (January 2022 to December 2022). (a) As a first attempt, you decided to use a Multiplicative Trend-Seasonal Model (also called Winters Model) Use method discussed in class to estimate initial (at time 0) Level (L0), Trend (T0), and all sessional factors using oldest two years data. (b) Using estimates obtained in part (a), and smoothing constants =0.1,Y=0.2, and =0.2, apply the Multiplicative Trend-Seasonal Model to your data (starting at time 0 ) and compute Mean \% Error, Mean Absolute \% Error, RMSE (Root Mean Square Error), and other indicators. Discuss what information these indicators provide. (Create your own spreadsheet - you can get some ideas from the spreadsheet for class example posted on canvas) (c) Using the spreadsheet from part (b), Use SOLVER to find smoothing constants ,, and that minimizes RMSE. For model to be adoptive to changes, you will like all three smoothing constants (,, and ) to be at least 0.1. (d) Using your model from part ( c ), forecast Airport Passenger flow for next 12 months. How good do you think is your forecast? As a manager of a regional airport you need to forecast monthly passenger flow (number of passengers flying in and out) through the airport for planning and budgeting purposes. You have historical monthly airport passenger data over last five years - ending in December, 2021 (download EXCEL file Airport_Passenger_data.xlsx from Canvas). You want to explore the idea of exponential smoothing to model the history and prepare a forecast for the following year (January 2022 to December 2022). (a) As a first attempt, you decided to use a Multiplicative Trend-Seasonal Model (also called Winters Model) Use method discussed in class to estimate initial (at time 0) Level (L0), Trend (T0), and all sessional factors using oldest two years data. (b) Using estimates obtained in part (a), and smoothing constants =0.1,Y=0.2, and =0.2, apply the Multiplicative Trend-Seasonal Model to your data (starting at time 0 ) and compute Mean \% Error, Mean Absolute \% Error, RMSE (Root Mean Square Error), and other indicators. Discuss what information these indicators provide. (Create your own spreadsheet - you can get some ideas from the spreadsheet for class example posted on canvas) (c) Using the spreadsheet from part (b), Use SOLVER to find smoothing constants ,, and that minimizes RMSE. For model to be adoptive to changes, you will like all three smoothing constants (,, and ) to be at least 0.1. (d) Using your model from part ( c ), forecast Airport Passenger flow for next 12 months. How good do you think is your forecast