Practice Final Exam Part1 (Closed Book): Regression
Analysis - ISYE-6414-OAN/A/QS
Due No due date Points 26 Questions 26 Available after Jul 19 at 8am Time Limit 90 Minutes
Allowed Attempts Unlimited
This quiz is no longer available as the course has been concluded.
Attempt History
Attempt Time Score
LATEST Attempt 1 7 minutes 17 out of 26
Submitted Jul 30 at 6:05pm
Question 1 pts
If the constant variance assumption does not hold in multiple linear regression, we apply a Box-Cox transformation
to the predicting variables.
You Answered True
Correct Answer False
3.11. Assumptions and Diagnostics
If constant variance or normality assumptions do not hold, we apply a Box-Cox transformation to the response
variable.
Question 2 pts
Multicollinearity in multiple linear regression means that the columns in the design matrix are linearly
independent.
True
False
Correct!
3.13. Model Evaluation and Multicollinearity
Multicollinearity means there is a dependency between predicting variables which would
equate to the columns in the design matrix.
Question 3 pts
,
Analysis - ISYE-6414-OAN/A/QS
Due No due date Points 26 Questions 26 Available after Jul 19 at 8am Time Limit 90 Minutes
Allowed Attempts Unlimited
This quiz is no longer available as the course has been concluded.
Attempt History
Attempt Time Score
LATEST Attempt 1 7 minutes 17 out of 26
Submitted Jul 30 at 6:05pm
Question 1 pts
If the constant variance assumption does not hold in multiple linear regression, we apply a Box-Cox transformation
to the predicting variables.
You Answered True
Correct Answer False
3.11. Assumptions and Diagnostics
If constant variance or normality assumptions do not hold, we apply a Box-Cox transformation to the response
variable.
Question 2 pts
Multicollinearity in multiple linear regression means that the columns in the design matrix are linearly
independent.
True
False
Correct!
3.13. Model Evaluation and Multicollinearity
Multicollinearity means there is a dependency between predicting variables which would
equate to the columns in the design matrix.
Question 3 pts
,