FREE Lean Six Sigma Green Belt DMAIC: Analyze Phase Techniques Questions and Answers Flashcards
6 cards from real Lean Six Sigma Green Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 6 FREE Lean Six Sigma Green Belt DMAIC: Analyze Phase Techniques Questions and Answers flashcards as text
During the Analyze phase, what is the correct sequence for validating a potential root cause?
Answer: Brainstorm causes, prioritize with data, verify with statistical analysis
Root cause validation follows brainstorming potential causes, narrowing them with data, and confirming with statistical tools.
Which statistical test is most appropriate for analyzing the relationship between two categorical variables?
Answer: Chi-square test
The chi-square test evaluates whether there is a significant association between two categorical variables.
In regression analysis during the Analyze phase, what does the R-squared value represent?
Answer: The percentage of variation in the response variable explained by the predictor
R-squared indicates the proportion of variability in the dependent variable that is accounted for by the independent variable(s).
What is the 'Five Whys' technique best suited for in the Analyze phase?
Answer: Drilling down to the root cause of a problem through iterative questioning
The Five Whys technique repeatedly asks 'why' to peel back layers of symptoms and reach the fundamental root cause.
Which tool helps a Green Belt team narrow down many potential causes to the critical few for further analysis?
Answer: Cause-and-effect matrix (C&E matrix)
The C&E matrix ranks potential causes against key outputs to prioritize which Xs have the greatest impact on Ys.
What assumption must be verified before conducting a two-sample t-test in the Analyze phase?
Answer: The data from both samples are approximately normally distributed
A two-sample t-test requires that both populations are approximately normally distributed, especially important for small samples.