A data scientist is performing a linear regression and wants to construct a model that...

→ R² (coefficient of determination) quantifies how much of the variance in the dependent variable is explained by the model. A higher R² means a better fit to the data, making it the metric to maximize for explanatory power in regression analysis.

Why the other options are incorrect:

A: Accuracy is used in classification, not regression.

C: p-values test statistical significance of coefficients, not overall model fit.

D: AUC (Area Under the Curve) applies to classification models, not regression.

Official References:

CompTIA DataX (DY0-001) Study Guide – Section 3.2:“R² is a regression performance metric indicating the proportion of variance explained by the independent variables.”