Basic forecasts You have monthly sales data on surfboards ranging from January 2017 to September 2018. The data is not seasonally adjusted. 4 Your supervisor asked you to forecast sales for the next few 3 months. The data follows. 2017-01-01 6459 2017-02-01 6527 2017-03-01 6634 2017-04-01 6816 2017-05-01 6990 2017-06-01 7157 2017-07-01 7197 2017-08-01 7228 2018-01-01 6692 2018-02-01 6799 2018-03-01 6889 2018-04-01 7081 2018-05-01 7283 2018-06-01 7442 2018-07-01 7496 2018-08-01 7525 2018-09-01 7477 2017-09-01 7177 2017-10-01 7182 2017-11-01 7117 2017-12-01 6970 The instructor will show you a time series plot of the variable and a correlogram. 1. The training set will now be set to the end of 2017. Create forecasts (mean, naive, naive with drift and seasonal naive). Which approach works best from a visual perspective? The instructor will show you the forecasts graphically. 2. Now compute the RMSE, MAE, MPE, and MAPE for each method. Which forecasting method would you use based on your measures of forecast accuracy? 3. Now make your three forecasts. One for October November and December with your favorite method.