LSS Black Belt · PeopleCert · Analyze · Bank updated 2026-09-22
LSS Black Belt practice questions: Analyze
5 free questions from 31 on this area · answer and explanation for each · no sign-up
These 5 questions come from the Analyze section of our LSS Black Belt bank (31 questions on this area, which carries 20% of the real exam). Every question is original, with the correct answer explained and linked to the source it is drawn from.
Free: 6 questions in study mode, no card. All 31 Analyze questions and the full LSS Black Belt bank: $15 one-time.
1/5 · Analyze · easy
A Black Belt wants to estimate average call-handling time across a call center that has four distinct call types with very different average durations. To ensure every call type is proportionally represented in the sample rather than relying on chance, which sampling method should be used?
ASimple random sampling from the entire population of calls
BConvenience sampling of whichever calls are easiest to record
CSystematic sampling by selecting every 10th call regardless of type
DStratified random sampling, sampling proportionally within each call type
2/5 · Analyze · hard
A two-way ANOVA examines the effects of Machine (2 levels) and Shift (3 levels) on output yield. The Machine x Shift interaction term has a p-value of 0.02 at alpha = 0.05, while both main effects (Machine and Shift individually) are non-significant. What is the correct interpretation?
AThe interaction p-value is invalid because at least one main effect must be significant for an interaction to be tested
BThe design should be discarded and replaced with a one-way ANOVA
CThe effect of Machine on yield depends on which Shift it operates in, so the main effects should not be interpreted in isolation
DBecause both main effects are non-significant, the significant interaction result should be ignored
3/5 · Analyze
A Black Belt is designing a hypothesis test to detect a specific shift in a process mean. Holding the sample size, the effect size to be detected, and the population standard deviation all constant, which single action would increase the statistical power of the test?
AIncrease the amount of measurement system variation contributing to the data collected.
BDeliberately widen the confidence interval associated with the beta risk calculation.
CLower the significance level (alpha), for example from 0.05 to 0.01, to make the test more rigorous.
DRaise the significance level (alpha), for example from 0.01 to 0.05, which makes it easier to reject a false null hypothesis and reduces beta risk.
Answer: D. In the alpha/beta/power framework, for a fixed sample size, effect size, and variance, power and beta risk trade off directly against alpha: raising alpha increases the rejection region and thus power, while lowering alpha shrinks power. Black Belts must weigh this trade-off because the only other levers for increasing power — larger sample size or reduced variability — were held constant in this scenario.
Source: the IASSC Lean Six Sigma Black Belt Body of Knowledge (ILSSBOK BB, PeopleCert syllabus v1.0) — Analyze
4/5 · Analyze
A Black Belt runs a One-Way ANOVA comparing average cycle time across four production lines and obtains a p-value of 0.01 against a stated alpha of 0.05. Which conclusion is correctly supported by this result alone?
AThree of the four lines are statistically equivalent and one line is confirmed as the sole root cause of the difference.
BThe variance in cycle time is identical across all four lines.
CAll four production lines have significantly different mean cycle times from every other line.
DAt least one production line's mean cycle time differs significantly from at least one other line; identifying which specific lines differ requires further comparison.
Answer: D. A significant One-Way ANOVA F-test rejects the null hypothesis that all group means are equal, indicating that at least one group mean differs from at least one other. It does not, by itself, indicate which specific groups differ or confirm equal variances; identifying the differing pair(s) requires additional comparison work beyond the single omnibus p-value.
Source: the IASSC Lean Six Sigma Black Belt Body of Knowledge — Analyze
5/5 · Analyze
A Black Belt wants to determine whether defect type (Scratch, Dent, or Discoloration) is associated with which of three production shifts produced the part, using counts organized in a 3x3 contingency table. Which hypothesis test should be used, and what does a significant result indicate?
ATwo-Sample t-test; a significant result would indicate the shifts have different average defect counts.
BSimple linear regression; a significant slope would indicate that shift number causes a specific defect type.
COne-Way ANOVA; a significant result indicates that at least one shift has a significantly different defect type than the others.
DChi-Square test of independence; a significant result indicates that defect type and shift are not independent, i.e., the distribution of defect types differs across shifts.
Answer: D. When both variables of interest are categorical and organized as counts in a contingency table, the Chi-Square test of independence is the appropriate tool. A significant p-value indicates that the observed distribution of defect types differs across shifts more than would be expected if the two categorical variables were independent.
Source: the IASSC Lean Six Sigma Black Belt Body of Knowledge — Analyze
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