In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. ![]() This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable. The case of one explanatory variable is called simple linear regression for more than one, the process is called multiple linear regression. In statistics, linear regression is a linear approach for modelling the relationship between a scalar response and one or more explanatory variables (also known as dependent and independent variables). ![]() Statistical modeling method Part of a series on
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