Interpreting a Residual Plot

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After fitting a linear regression, you plot residuals against the fitted values and see a clear funnel shape — residuals are small and tightly clustered for low fitted values, and spread out much wider for high fitted values. What does this pattern indicate, and why does it matter?

Multiple Choice

The funnel shape indicates the model is overfitting the training data The funnel shape indicates heteroscedasticity — non-constant error variance — which makes standard errors, p-values, and confidence intervals unreliable The funnel shape means the relationship between predictors and target is non-linear The funnel shape is expected and requires no correction as long as R-squared is high

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Interpreting a Residual Plot

Multiple Choice

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