The intercept in the regression model represents the mean value of the response variable when all the predictor variables in the model are equal to zero, and it serves as the starting point for evaluating the effects of the independent variables on the dependent variable.
In business terms, an intercept reflects the portion of the dependent variable not influenced by independent variables. It quantifies the impact of changes in independent variables from the baseline value, offering insights into the starting point for evaluating effects.
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