OPTIONS Separate the variables and conduct a Simple Linear Regression Drop the predictor that is causing the high VIF and then re-do Regression Live with the variable having high VIF and hope that it is a model adequacy issue Try doing a Curvilinear Regression ANSWER...
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OPTIONS Mallows Cp Adjusted R2 R2 Predicted R2 ANSWER Predicted R2 EXPLANATION The other three are not serious considerations.
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OPTIONS Correlated Auto-correlated Collinear Confounded ANSWER Collinear EXPLANATION Collinear means correlated to each other unless they auto-correlate
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OPTIONS The Upper Whisker is at 33.0 The Data could be skewed The data forms a normal distribution The Lower Whisker is at 30 ANSWER The Data could be skewed EXPLANATION Option a and d are visible from the Box Plot, but in terms of...
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OPTIONS Brainstorming Affinity Diagram Cause and Effect Diagram Cause and Effect Matrix ANSWER Cause and Effect Diagram EXPLANATION The CE Diagram is the best possible tool here.
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OPTIONS Normal Distribution Poisson Distribution Hypergeometric Distribution Chi-Square Distribution ANSWER Normal Distribution EXPLANATION For large sample sizes, the Binomial distribution moves to the normal distribution.
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OPTIONS 0.66 0.62 0.6 0.5 ANSWER 0.66 EXPLANATION Applying standard binomial formula with p = 0.02 and x = 0.
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i. The process is in control ii. The process may not have been in control iii. The process may not have been normal OPTIONS i and ii ii and iii i, ii and iii Correct Option:B ii and iii EXPLANATION Such a condition can only...
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ANSWER Reduce variations Center the mean Bring the process in statistical control The choice of what to do rests with the Black Belt ANSWER Reduce variations EXPLANATION Cp value less than 1 automatically indicates that variations are high in the process
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OPTIONS 0.5 1 1.5 2 ANSWER 1 EXPLANATION The Cp is 1 as derived by applying standard Cp formula.
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