Reference no: EM132849196

Question 1

What is a residual for a multiple regression model and the data that is used to create it? Select one.

• A statistic that is used to evaluate the significance of the multiple regression model
• The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression model
• The predicted value of the response variable using the multiple regression model
• A statistic that explains the relationship between response and predictor variables

Question 2

Which of the following correctly shows the general form of a multiple regression model? Select one.

Question 3

Which of the following choices correctly identifies the following Q-Q plots for the normality of residuals assumption? Select one.

• Graphs A and B both show residuals with distributions that closely approximate a Normal distribution.
• Graph B shows residuals with a distribution that more closely approximates a Normal distribution than Graph A.
• Both graphs show residuals with a distribution that is not Normal.
• Graph A shows residuals with a distribution that more closely approximates a Normal distribution than Graph B.

Question 4

The ols() method in statsmodels module is used to fit a multiple regression model using "Exam4" as the response variable and "Exam1", "Exam2", and "Exam3" as predictor variables. The output is shown below. A text version is available. What is the correct regression equation based on this output and what is the coefficient of determination? Select one.

Question 5

Suppose a multiple regression model is fitted into a variable called model. Which Python method below returns residuals for a data set based on a multiple regression model? Select one.