Download Certified Lean Six Sigma Green Belt - GAQM.CLSSGB.Prep4Sure.2018-08-19.120q.vcex

Vendor: GAQM
Exam Code: CLSSGB
Exam Name: Certified Lean Six Sigma Green Belt - GAQM
Date: Aug 19, 2018
File Size: 52 KB
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Demo Questions

Question 1
Which statement(s) are correct for the Regression Analysis shown here? (Note: There are 2 correct answers).
  1. This Regression is an example of a Multiple Linear Regression.
  2. This Regression is an example of Cubic Regression.
  3. %Cu explains the majority of the process variance in heat flux.
  4. Thickness explains over 80% of the process variance in heat flux.
  5. The number of Residuals in this Regression Analysis is 26.
Correct answer: AD
Question 2
The Regression Model for an observed value of Y contains the term ?o which represents the Y axis intercept when X = 0.
  1. True
  2. False
Correct answer: A
Question 3
Which statement(s) are true about the Fitted Line Plot shown here? (Note: There are 2 correct answers).
  1. When Reactant increases, the Energy Consumed increases.
  2. The slope of the equation is a positive 130.5.
  3. The predicted output Y is close to -18 when the Reactant level is set to 6.
  4. Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Correct answer: CD
Question 4
After reviewing the Capability Analysis shown here select the statement(s) that are untrue.
  1. The process is properly assumed to be a Normal process
  2. The Mean of the process moving range is 1.78
  3. The process is out of Control
  4. This Capability Analysis used subgroups
  5. Majority of the dimensional values are outside of the tolerance than within
Correct answer: A
Question 5
The actual experimental response data varied somewhat from what a Belt had predicted them to be. This is the result of which of these?
  1. Inefficiency of estimates
  2. Residuals
  3. Confounded data
  4. Gap Analysis
Correct answer: B
Question 6
Multiple Linear Regressions (MLR) is best used when which of these are applicable? (Note: There are 3 correct answers).
  1. Non-linear relationships between the inputs X’s and output Y
  2. Uncertainty in the slope of the linear relationship between an X and a Y
  3. Relationships between Y (output) and more than one X (Input)
  4. Preventing the use of a Designed Experiment if unnecessary
  5. We assume that the X’s are independent of each other
Correct answer: CDE
Question 7
The generation of a Regression Equation is justified when we _____________. (Note: There are 4 correct answers).
  1. Expect the relationship to be Linear between the output and inputs
  2. Know that there is a non-linear relationship between output and input(s)
  3. Need to understand how to control a process output by controlling the input(s)
  4. Experience several process defects and have no other way to fix them
  5. When it is very expensive or too late to measure the output
Correct answer: ACDE
Question 8
Which statement(s) are correct for the Regression Analysis shown here? (Note: There are 2 correct answers).
  1. Regression is an example of a Multiple Linear Regression.
  2. This Regression is an example of Cubic Regression.
  3. %Cu explains the majority of the process variance in heat flux.
  4. Thickness explains over 80% of the process variance in heat flux.
  5. The number of Residuals in this Regression Analysis is 26.
Correct answer: AD
Question 9
The Regression Model for an observed value of Y contains the term to which represents the Y axis intercept when X = 0.
  1. True
  2. False
Correct answer: A
Question 10
Which statement(s) are true about the Fitted Line Plot shown here? (Note: There are 2 correct answers).
  1. When Reactant increases, the Energy Consumed increases.
  2. The slope of the equation is a positive 130.5.
  3. The predicted output Y is close to -18 when the Reactant level is set to 6.
  4. Over 85 % of the variation of the Energy Consumed is explained by the Reactant via this Linear Regression.
Correct answer: CD
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