DS AdvancedLesson 22Free preview
DS Regression Coefficients
This lesson is part of Data Science · All levels
Summary
The regression coefficient explains the magnitude of the effect of each predictor variable on the target: one increase in the predictor unit is associated with a change in the target average by the same coefficient, with the other variable being fixed. The negative coefficient indicates a relationship to the inverse. To avoid misinterpretation, the coefficients must be read together with the error standard and the p-value.
Key points
- Coefficient = change in the mean of the target per unit predictor (ceteris paribus).
- The positive coefficient: in the direction; the negative coefficient: in the direction opposite.
- P-value > 0.05 means that the coefficient is not significantly different from zero.
- The coefficients alone do not indicate the reliability of the estimate.
- Combine the coefficients, std err, and p-value when interpreting.
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