DMAIC: Analyze Phase Techniques Flashcards
7 cards from real Lean Six Sigma Green Belt Certification practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 7 DMAIC: Analyze Phase Techniques flashcards as text
A Green Belt notices that a process produces more defects on Monday mornings than other times. Which stratification analysis should be performed first?
Answer: Time-based stratification by shift and day
Time-based stratification breaks data into segments (shift, day, week) to reveal patterns linked to specific conditions like Monday morning starts.
In hypothesis testing for a Green Belt project, a p-value of 0.03 is obtained with α = 0.05. What is the correct conclusion?
Answer: Reject the null hypothesis
Since p-value (0.03) < α (0.05), there is sufficient evidence to reject the null hypothesis.
Which tool is BEST used to quantify the relationship strength between a continuous X variable and a continuous Y variable during the Analyze phase?
Answer: Pearson correlation coefficient
Pearson correlation coefficient measures the strength and direction of a linear relationship between two continuous variables.
A team uses a multi-vari chart and finds that variation is greatest between different machines compared to within-machine or time-based variation. This indicates which type of variation source?
Answer: Positional variation
Variation between different machines (or positions/fixtures) is classified as positional variation in a multi-vari study.
During the Analyze phase, a team wants to determine whether training (yes/no) affects defect rate (defective/not defective). Which statistical test is most appropriate?
Answer: Chi-square test of independence
Chi-square test of independence is used when both the input and output variables are categorical (attribute data).
What does a steep slope on a Pareto chart's cumulative percentage line early in the chart indicate?
Answer: A few categories account for the majority of defects
A steep early cumulative line confirms the 80/20 principle — a few categories drive most of the defects.
In regression analysis, a coefficient of determination (R²) of 0.85 means:
Answer: 85% of the variation in Y is explained by the X variable(s) in the model
R² represents the proportion of variance in the response variable (Y) that is explained by the predictor variable(s) in the regression model.