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ISYE 6414 Final Exam Review Questions With Correct Verified Answers A+ Graded $13.49   Add to cart

Exam (elaborations)

ISYE 6414 Final Exam Review Questions With Correct Verified Answers A+ Graded

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  • Course
  • ISYE 6414
  • Institution
  • ISYE 6414

Least Square Elimination (LSE) cannot be applied to GLM models. - ANS False - it is applicable but does not use data distribution information fully. In multiple linear regression with idd and equal variance, the least squares estimation of regression coefficients are always unbiased. - ANS T...

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  • September 8, 2024
  • 15
  • 2024/2025
  • Exam (elaborations)
  • Questions & answers
  • ISYE 6414
  • ISYE 6414
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C
LO
YC
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U
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ISYE 6414 Final Exam Review
Questions WithCorrect Verified
Answers A+ Graded

, Least Square Elimination (LSE) cannot be applied to GLM models. -
ANS False - it is applicable but does not use data distribution
information fully.

In multiple linear regression with idd and equal variance, the least
squares estimation of regression coefficients are always unbiased. -




K
ANS True - the least squares estimates are BLUE (Best Linear
Unbiased Estimates) in multiple linear regression.




C
Maximum Likelihood Estimation is not applicable for simple linear



LO
regression and multiple linear regression. - ANS False - In SLR and
MLR, the SLE and MLE are the same with normal idd data.

The backward elimination requires a pre-set probability of type II error
YC
- ANS False - Type I error

The first degree of freedom in the F distribution for any of the three
procedures in stepwise is always equal to one. - ANS True
D


MLE is used for the GLMs for handling complicated link function
U


modeling in the X-Y relationship. - ANS True
ST




In the GLMs the link function cannot be a non linear regression. -
ANS False - It can be linear, non linear, or parametric

When the p-value of the slope estimate in the SLR is small the
r-squared becomes smaller too. - ANS False - When P value is
small, the model fits become more significant and R squared become
larger.

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