What does the intercept indicate in a regression equation?

In a regression equation, the intercept represents the expected value of the dependent variable when all independent variables are equal to zero. In practical terms, it serves as the starting point for the regression line on a graph. The intercept indicates where the line crosses the y-axis, which provides insight into the baseline value of the dependent variable without any influence from the independent variables.

This understanding is vital for interpreting regression models, as it sets the foundation for understanding how changes in the independent variables will affect the dependent variable. The intercept allows researchers and analysts to contextualize their findings by providing a reference point from which to measure the effects of the independent variables.

Understanding the role of the intercept is crucial for effective data analysis, especially when making predictions or drawing conclusions based on the regression results.