Lean Six Sigma Green Belt Certification Basic Statistical Tools 5

Question 1

Which central limit theorem property allows the use of normal-distribution-based control charts even when the underlying data are non-normal?

Accepted Answer

Sample means approach a normal distribution as sample size increases

Answer

The Central Limit Theorem states that the distribution of sample means becomes approximately normal as n increases, regardless of the population distribution.

Question 2

A Gauge R&R study reveals that measurement system variation accounts for 28% of total observed variation. What action is most appropriate?

Accepted Answer

Improve or replace the measurement system before collecting process data

Answer

A %GR&R above 30% is unacceptable; 28% is in the marginal zone and improvement is strongly recommended before analysis.

Question 3

What does the standard error of the mean (SEM) measure?

Accepted Answer

How much sample means vary from the population mean across repeated samples

Answer

SEM = σ / √n, representing how much the sample mean is expected to vary from the true population mean.

Question 4

A process has Cp = 1.50 and Cpk = 0.80. What does this tell you?

Accepted Answer

The process has adequate spread but is significantly off-center

Answer

High Cp with low Cpk indicates the process spread fits within specs but the mean is shifted toward or beyond one limit.

Question 5

When should a nonparametric statistical test be used instead of a parametric test?

Accepted Answer

When the data are ordinal or clearly non-normal with small sample sizes

Answer

Nonparametric tests make no normality assumption and are appropriate for ordinal data or non-normal distributions, especially with small samples.

Lean Six Sigma Green Belt Certification Practice Test

Lean Six Sigma Green Belt Certification Practice Test

Lean Six Sigma Green Belt Certification Basic Statistical Tools 5