Gives a definitive line of best fit
Makes efficient use of data and good results can be obtained with relatively small amounts of data
Many processes are linear and so are well described by regression analysis Disadvantages
Assumes linearity betweenx and y
The observations used may be atypical
Historic data is used and patterns may change in future
Each observation should be independent from the others
Forecasting usually involves extrapolation outside the given range of observations where working conditions and therefore cost patterns may change