The first class of forecasting methods we cover are based on “averaging” past time series values to forecast. Restricting attention first to Moving Average and Single Exponential Smoothing (SES) methods, explain the difference between these two approaches. For what types of time series would these methods be most suitable (hint: think in terms of dominant time series components present)? Would these methods be appropriate for the example of healthcare? Explain why with evidences