The Root Mean Square error is a measure of the deviation of the forecasted value from the actual value. In Root Mean Square the deviations are summed and then divided by the number of time periods in the time series. Lastly, the square root of this quantity is evaluated. The Root Mean Square is used to quantitatively measure how closely the forecasted variable tracks the actual data. The magnitude of the Root Mean Square error can be evaluated only by comparing it to the mean of the time series.