Question

Principal components or factor analytic models on covariates are often useful for reducing complex covariate spaces. (a) True (b) False The question was posed to me at a job interview. Question is taken from Binary and Count Outcomes in portion Statistical Inference and Regression Models of Data Science Select the correct answer from above options Data Science questions and answers, Data Science questions pdf, Data Science question bank, Data Science questions and answers pdf, mcq on Data Science pdf, Data Science questions and solutions, Java mcq Test , Interview Data Science questions, Data Science Questions for Interview, Data Science MCQ (Multiple Choice Questions),Core Data Science Questions, Core Data Science MCQ,core Data Science interview questions for experiencedcore Data Science interview questions for 3 years experience,Data Science programming questions,core Data Science interview questions for freshers,Data Science interview questions and answers for freshers, Data Science programming questions and answers pdf, Data Science interview questions for beginners

Answer 1

Correct option is (a) True To explain: The space of models explodes quickly as you add interactions and polynomial terms.