In the simple linear regression model, the regression slope: (A) indicates by how many units Y increases, given a one-unit increase in X. (B) when multiplied with the explanatory variable will give you the predicted Y. (C) indicates by how many percent Y increases, given a one percent increase in X. (D) represents the elasticity of Y on X.

(A) indicates by how many units Y increases, given a one-unit increase in X.

Step-by-step explanation:

The form for simple linear regression model for outcome y which is a function of predictor x is:

y = β₀ + β₁x + ε

For this model, β₀ is population parameter which corresponds to intercept and β₁ is the true population slope coefficient which is defined as predicted increase in the y for a unit increase in the x.

Hence option (A) indicates by how many units Y increases, given a one-unit increase in X is correct.