1. Exercise One: Using the Forecasting Data with Exponential Smoothing Module as your guide and the given time series below, (a) forecast the values for the time series, including the month of January, using an arbitrary value for alpha (i.e. between zero and one), (b) compute the error for your time series, (c) find the absolute error, (d) compute the squared error, (e) find the absolute percentage error, (f) use the GRG Non-Linear Solver - as shown in class to find the value of alpha that minimizes the Mean Absolute Percentage Error, (g) graph the Actual versus the Forecast for your time series, (h) do you perceive any seasonality in the series by visual inspection? Observation 1 2 3 5 6 7 8 9 10 11 12 Month January February March April May June July August September October November December Actual Sales 24 28 27 24 26 29 25 27 31 26 30 34 1. Exercise One: Using the Forecasting Data with Exponential Smoothing Module as your guide and the given time series below, (a) forecast the values for the time series, including the month of January, using an arbitrary value for alpha (i.e. between zero and one), (b) compute the error for your time series, (c) find the absolute error, (d) compute the squared error, (e) find the absolute percentage error, (f) use the GRG Non-Linear Solver - as shown in class to find the value of alpha that minimizes the Mean Absolute Percentage Error, (g) graph the Actual versus the Forecast for your time series, (h) do you perceive any seasonality in the series by visual inspection? Observation 1 2 3 5 6 7 8 9 10 11 12 Month January February March April May June July August September October November December Actual Sales 24 28 27 24 26 29 25 27 31 26 30 34