Simple linear regression, like ARIMA, involves statisticalmodeling. Unlike decomposition, averaging and smoothing methods,fitting a simple linear regression model to data involvesstatistical inference.
Moreover, several assumptions/conditions need to be satisfied inorder to use a simple linear regression model. One might think thatthis added level of complexity would make regression analysis lesslikely to be used in practice. On the contrary, it is widely usedby management.  Why do you suppose this is the case? Whatadvantages does simple linear regression have over the forecastingmethods we've covered so far? Can you give an example of how simplelinear regression may be used in your area of employment and/orexpertise?
