ISYE 6414 FINAL EXAM 2024 / ISYE6414 FINAL EXAM ACTUAL EXAM QUESTION AND VERIFIED ANSWERS ALREADY GARDED A+

Mary has a dataset with height (in inches), weight (in lbs), and math_score (final exam score out of 100) of 300 students in an undergraduate math course. She creates another field called BMI (Body Mass Index) calculated as BMI=703*(weight/height2). She wants to examine if math_scoreis related to height, weight and BMI. She plans to use a linear regression model math_score ~ height+weight+BMI to study this relationship. Leonard hears about Mary’s plan and tells Mary that BMI should not be used in her experimentbecause it is created from the height and weight variables which are already included in the model. He says this leads to an issue called multicollinearity in linear regression. Which of the below options is TRUE? a. Leonard is right; retaining height, weight, BMI in the model will definitely lead tomulticollinearity. b. Leonard is wrong because BMI is not a linear combination of weight and height. c. Leonard is wrong; it is impossible to say whether multicollinearity is a problem in aproposed model without first fitting the model. d. Leonard is right, but the correct name for this issue is homoscedasticity