Used to define a functional relationship between two or more correlated variables.
The relationship is developed from observed data where the independent variable is used to predict the dependent variable.
Linear regression refers to a special class of regression where the relationship between the variables is assumed to be represented by a straight line.
Linear regression analysis is useful for long-term forecasting of major occurrences and aggregate planning.
The major restriction in using linear regression forecasting is that past data and future projections are assumed to fall around a straight line.
If the dependent variable changes due to the change in the independent variable, it is a causal relationship.
A measure of how well the data fits the regression line can be determined by calculating the standard error of estimate.
Standard error of estimate: reflects how widely the errors are dispersed around the regression line.