![]() ![]() Most commonly, the conditional mean of the response given the values of the explanatory variables (or predictors) is assumed to be an affine function of those values less commonly, the conditional median or some other quantile is used. 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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