Time series in healthcare analysis

However, errors tend to increase in extrapolation forecasting when long-range forecasts are considered. To determine if a variable can be used in extrapolation forecasting model it must first be established that the said variables in the future can conform to similar patterns as experienced in the past. In terms of effectiveness and cost extrapolation methods of forecasting are reliable, inexpensive, often very objective and they are easy to automate as such are widely used especially in for production and inventory forecasting (Armstrong, 2001). Extrapolation is also used in population forecasting. The method however required careful techniques of selecting and preparing of data, careful seasonal adjustment of the variables, extrapolation techniques need to be measured carefully to meet data requirement and one requires to access for uncertainty in the data and prediction made using the technique.