please select all the correct answers.

1. [2 pts] What can we say about the linear regression model Y ~ 1 + X1 + X2 with a MultipleR" value of 0.49? Please select ALL that apply. It's possible that there is only one correct answer. A. The sample correlation r between the fitted values y, and the responses y, is 0.49. B. The sample correlation r between the fitted values y, and the responses y, is 0.7. C. The Residual Sum of Square for the model Y ~ 1 + X1 + X2 is 51% as large as the Residual Sum of Square for the null model Y ~ 1. D. The Residual Sum of Square for the model Y ~ 1 + X1 + X2 is 49% as large as the Residual Sum of Square for the null model Y ~ 1. 2. [2pt] Based on the fitted model log(Y) = 2 - 0. 4x, which of the following statements is true? Please select the best answer. Note: The log is natural logarithm. Here are a few computed values that may be relevant -04 - 1 = - 0.330, e - 1 = 0.492 A. When X increases by 1 unit, Y decreases by 0.330 units on average. B. When X increases by 1 unit, Y decreases by 0.492 units on average. C. When X increases by 1 unit, Y decreases by 33.0% on average. D. When X increases by 1 unit, Y decreases by 49.2% on average. 3. [2pt] The following model uses the Type ("Luxury" vs. "Common") and the Mileage (miles) to predict the Price ($) of a car: Price ~ 1 + Type + Mileage Based on the model, which of the following statements is/are correct? Please select ALL that apply. It's possible that there is only one correct answer. A. For each type, the impact of the mileage on the car's price is the same B. For each type, the impact of the mileage on the car's price is different C. For each type, the price for a new car (i.e., Mileage = 0) is the same D. For each type, the price for a new car (i.e., Mileage = 0) is the different