The y-intercept of a linear regression relationship represents the value of one variable when the value of the other is 0. A linear regression equation takes the same form as the equation of a line, and it's often written in the following general form: y A + Bx Here, ‘x’ is the independent variable (your known value), and ‘y’ is the dependent variable (the predicted value). Linear regression is graphically depicted using a straight line with the slope defining how the change in one variable impacts a change in the other. ![]() Each independent variable in multiple regression has its own coefficient to ensure each variable is weighted appropriately.Īlso called simple regression, linear regression establishes the relationship between two variables.Whereas linear regress only has one independent variable impacting the slope of the relationship, multiple regression incorporates multiple independent variables.Multiple regression is a broader class of regressions that encompasses linear and nonlinear regressions with multiple explanatory variables. ![]()
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