Doug Wanted to Use Simple Linear Regression to Study the Relation

Multiple Choice

Doug wanted to use simple linear regression to study the relation between the time to complete a marathon (in hours) (Y) and the fluid intake (in ml) during the race (X) . Based on the same data set, he estimated two models.
Model 1: X₁ = total amount of fluid intake; Y = .00028X₁ + 3.97. R₁² = .014.
Model 2: X₂ = amount of fluid intake per hour; Y = -.0052X₂ + 7.84. R₂² = .65.
Suppose for both models, all assumptions for linear regression are satisfied. Compare the two models.

A) Doug should use model 1, because the correlation between X₁ and Y is stronger than that between X₂ and Y (b_YX1 > b_YX2) .
B) Doug should use model 2, because it gives more accurate prediction of Y (the finishing time) than model 1 (R₁² < R₂²) .
C) Doug should use model 1, because model 2 will give unreasonable (negative) predicted values of Y when X is large.
D) Both models are problematic, because the units of X are different from the unit of Y.