Statistics - Intercept - Regression (coefficient|constant)

Thomas Bayes


Linear Equation

In a linear equation, the intercept is the point at which the line crosses the y-axis, otherwise known as the y-intercept

In the below linear equation, b below is the intercept: <MATH> y= mx + b </MATH>

Regression Analysis

In a regression analysis, the intercept or the regression coefficient <math>B_0</math> is the predicted score on Y when all predictors (X, Z) are zero.

The regression constants didn't make any sense in a lot of example because it doesn't make any sense to get zero for all others predictors (others variables not regression coefficients). It gives a meaningless regression constant <math>B_0</math> .

In contrast, if X=0 and Z=0 becomes the average then the regression coefficient <math>B_0</math> is going to be the predicted score on Y for an average score on all others predictors. That's a meaningful value.

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