Lean Six Sigma Green Belt Certification Analyze Phase Tools 2 — Questions and Answers
Question 1: A Green Belt notices that defects spike every Monday morning on the assembly line. Which Analyze phase tool best captures this time-based pattern?
- Scatter diagram
- Control chart (Correct answer)
- Box plot
- Regression analysis
Correct answer: Control chart
Control charts plot data over time and reveal periodic patterns such as day-of-week effects.
Question 2: Which statistical test should a Green Belt use to determine whether the mean output of Machine A is significantly different from Machine B?
- Chi-square test
- Two-sample t-test (Correct answer)
- ANOVA
- Mood's median test
Correct answer: Two-sample t-test
A two-sample t-test compares the means of two independent groups to determine statistical significance.
Question 3: In a regression model for predicting cycle time, the R-squared value is 0.82. What does this indicate?
- 82% of defects are explained by the model
- 82% of the variation in cycle time is explained by the predictors (Correct answer)
- The model is 82% accurate in predictions
- 18% of data points fit the regression line
Correct answer: 82% of the variation in cycle time is explained by the predictors
R-squared represents the proportion of variance in the response variable explained by the predictor variables.
Question 4: A team uses a fault tree analysis (FTA) during the Analyze phase. What is the primary purpose of FTA?
- To prioritize defects by frequency
- To map the logical chain of causes leading to a top-level failure event (Correct answer)
- To calculate process capability
- To identify the critical path in a project schedule
Correct answer: To map the logical chain of causes leading to a top-level failure event
Fault tree analysis uses Boolean logic to trace how combinations of lower-level events can cause a top-level failure.
Question 5: When would a Green Belt prefer a non-parametric test over a parametric test during data analysis?
- When the sample size exceeds 30
- When data is normally distributed with equal variances
- When data is non-normal or the sample size is very small (Correct answer)
- When comparing more than two group means
Correct answer: When data is non-normal or the sample size is very small
Non-parametric tests make no distribution assumptions, making them appropriate for non-normal data or very small samples.
Question 6: A Green Belt creates a scatter plot of oven temperature vs. product hardness and observes points forming a curved (parabolic) pattern. What should be concluded?
- There is no relationship between the variables
- A linear regression model is sufficient
- The relationship is non-linear and may require a polynomial or transformation (Correct answer)
- The data contains outliers that must be removed
Correct answer: The relationship is non-linear and may require a polynomial or transformation
A curved pattern in a scatter plot signals a non-linear relationship, suggesting the need for polynomial regression or a data transformation.
Question 7: In a multi-vari study, which type of variation describes differences that occur across positions within the same unit (e.g., left vs. right side of a part)?
- Temporal variation
- Cyclical variation
- Positional variation (Correct answer)
- Unit-to-unit variation
Correct answer: Positional variation
Positional (within-unit) variation captures differences at different locations within a single piece or unit.
Lean Six Sigma Green Belt Certification Analyze Phase Tools 2
A Green Belt notices that defects spike every Monday morning on the assembly line.
Which Analyze phase tool best captures this time-based pattern?