Explain why you would or wouldn’t agree with each of the following statements: (a) In the presence of autocorrelation, least-square estimate will be biased (b) If the pairwise correlations among predictors are all close to 0, then, there exists no collinearity; (c) If we center the predictors, VIF would change; (d) AIC can be used to select the models which are not nested with each other

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Explain why you would or wouldn’t agree with each of the following statements: (a) In the presence of autocorrelation, least-square estimate will be biased (b) If the pairwise correlations among predictors are all close to 0, then, there exists no collinearity; (c) If we center the predictors, VIF would change; (d) AIC can be used to select the models which are not nested with each other; (e) With the same data, the model selected by R-square is the same as the model selected by RMS; (f) For multinomial logistic regression with response variables with k categories, we need to model k logit equations; (g) Odds ratio is between 0 and 1.
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