How does one interpret the coefficients in a multiple linear regression model?
- They show the average change in the dependent variable for a one unit change in the independent variable, ceteris paribus
- They show the correlation between the dependent and independent variables
- They show the error term in the regression model
- They show the total variation in the dependent variable explained by the independent variables
Each coefficient in a multiple linear regression model represents the average change in the dependent variable for a one unit change in the corresponding independent variable, while keeping all other independent variables constant. This is known as ceteris paribus, or "all else being equal."
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