**Time Series Analysis**

Time-series forecasting models attempt to predict the future based on past data. Fer example sales figures collected for each of the past six week can he used to forecast vale for the seventh week. Quarterly sales figures collected for the past several year can he u-ed to forecast the sales in future quarters.

We present here three types of time-series forecasting models: (a) simple moving

average, (b) weighted moving average, and (e) exponential smoothing.In order to determine

operational forecast forecasts the number of incoming calls and average handling time in half-hour increments full each day of the week using historical data as shown. This lore cast is done weekly.

which model is most appropriate to use the data should first be plotted on a graph. For example if the data points appear to be relatively level a moving average or exponential smoothing model would be appropriate if the data points show an underlying trend then exponential smoothing with trend adjustment would be appropriate. In addition the errors associated with each model should be calculated and the resulting errors compared.

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