In the simple linear regression model, the regression slope:(A) indicates by how many units Y increases, given a one-unit in
crease 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
<u>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. </u>
<u>Hence option (A) indicates by how many units Y increases, given a one-unit increase in X is correct.</u>
