Year Airfare 2004 402.26 2005 391.5 2006 405.48 2007 390.3 2008 400.27 2009 359.91 2010 383.48 2011 402.45 2012 406.13 2013 407.99 2014 411.67 2015 395.7 2016 361.94 2017 352.85 2018 346.49 In R language, 1) Conduct time series plot of the average airfare data. Question #1: What patterns do you notice in the time series plot of average annual airfare from 2004 to 2018? (a. horizontal pattern, b. clear upward trend, c. clear seasonal effects, d. clear downward trend) 2) Use a simple moving average with n = 3 (3 years) to calculate a forecast for the average airfare in 2019. Question #2: What is the 2019 forecast for average airfare using the simple moving average technique? (Round to two decimal places) 3) Based on the predicted values up to 2018, calculate accuracy measures (MAE, MSE, RMSE, and MAPE) for the simple moving average method. Question #3: What is the MAE for the simple moving average method?(Round to two decimal places)

In R language,
1) Conduct time series plot of the average airfare data. Question #1: What patterns do you notice in the time series plot of average annual airfare from 2004 to 2018? (a. horizontal pattern, b. clear upward trend, c. clear seasonal effects, d. clear downward trend)

2) Use a simple moving average with n = 3 (3 years) to calculate a forecast for the average airfare in 2019. Question #2: What is the 2019 forecast for average airfare using the simple moving average technique? (Round to two decimal places)

3) Based on the predicted values up to 2018, calculate accuracy measures (MAE, MSE, RMSE, and MAPE) for the simple moving average method. Question #3: What is the MAE for the simple moving average method?(Round to two decimal places)

4) Use a simple exponential smoothing with a smoothing constant of 0.2 to calculate a forecast for the average airfare in 2019.
Question #4: What is the 2019 forecast for average airfare using simple exponential smoothing with a smoothing constant of 0.2?
 

5) Based on the predicted values up to 2018, calculate accuracy measures (MAE, MSE, RMSE, and MAPE) for the simple moving average method. Question #5: What is the MAE for the simple exponential smoothing method with a smoothing constant of 0.2? (Round to two decimal places)
 

6) Use a simple exponential smoothing with a smoothing constant of 0.8 to calculate a forecast for the average airfare in 2019.
Question #6: What is the 2019 forecast for average airfare using simple exponential smoothing with a smoothing constant of 0.8?(Round to two decimal places)

7) Based on the predicted values up to 2018, calculate accuracy measures (MAE, MSE, RMSE, and MAPE) for the simple moving average method. Question #7: What is the MAE for the simple exponential smoothing method with a smoothing constant of 0.8? (Round to two decimal places)

Question #8: Reviewing the accuracy measure values for each of these forecasting attempts, which would you trust most to provide the most accurate forecast of 2019 average airfare? (a. Simple moving average, b.Exponential smoothing method with a smoothing constant of 0.2, c. Exponential smoothing method with a smoothing constant of 0.8)