Question 26
Domain 3: Train and evaluate modelsYou are a data scientist creating a linear regression model. You need to determine how closely the data fits the regression line. Which metric should you review?
Correct answer: D
Explanation
The coefficient of determination, or R-squared, measures how much of the variation in the dependent variable is explained by the regression line. It shows how closely the data fits the model, with higher values indicating a better fit.
Why each option is right or wrong
A. Recall
B. Root Mean Square Error
C. Mean absolute error
D. Coefficient of determination
The relevant statistic is the coefficient of determination, R², which is defined in linear regression as the proportion of total variance in the dependent variable explained by the fitted model. Under the standard regression identity, it ranges from 0 to 1 in ordinary least squares with an intercept, and values closer to 1 indicate the line accounts for more of the observed variation, which is exactly what is being assessed here.