Lean Six Sigma Yellow Belt Certification Statistical Thinking and Variation 1 — Questions and Answers
Question 1: What are the two main types of process variation recognized in Six Sigma?
- Controlled and uncontrolled variation
- Common cause and special cause variation (Correct answer)
- Internal and external variation
- Random and systematic variation
Correct answer: Common cause and special cause variation
Six Sigma distinguishes between common cause variation (inherent to the system) and special cause variation (assignable to a specific, identifiable factor).
Question 2: Which of the following is an example of special cause variation?
- Minor fluctuations in machine output due to normal wear
- Slight temperature differences in a controlled environment
- A damaged cutting tool producing oversized parts (Correct answer)
- Random measurement differences within specification limits
Correct answer: A damaged cutting tool producing oversized parts
A damaged cutting tool is a specific, identifiable event causing variation beyond the process baseline, making it a special (assignable) cause.
Question 3: Walter Shewhart's primary contribution to statistical thinking was developing a method to:
- Eliminate all variation from manufacturing processes
- Calculate the cost of poor quality
- Distinguish between common and special cause variation (Correct answer)
- Set customer specification limits
Correct answer: Distinguish between common and special cause variation
Shewhart developed Statistical Process Control and control charts specifically to help practitioners differentiate between common cause and special cause variation.
Question 4: A process that exhibits only common cause variation is described as:
- Incapable of meeting specifications
- Out of statistical control
- In a state of statistical control (Correct answer)
- Exhibiting assignable cause variation
Correct answer: In a state of statistical control
A process with only common cause variation is stable and predictable — it is said to be in a state of statistical control.
Question 5: Statistical thinking in Six Sigma is best described as:
- Applying complex formulas to every business decision
- Using statistics to prove processes are defect-free
- Recognizing that variation exists in all processes and can be measured and reduced (Correct answer)
- Eliminating the need for qualitative analysis
Correct answer: Recognizing that variation exists in all processes and can be measured and reduced
Statistical thinking is a framework that acknowledges variation is inherent in all processes and that data-driven analysis is the key to understanding and improving them.
Question 6: What is the appropriate response when a process displays only common cause variation but does not meet customer specifications?
- React to individual defective parts by adjusting the machine
- Investigate and remove the special cause immediately
- Redesign or fundamentally change the process system (Correct answer)
- Widen the specification limits to accept current output
Correct answer: Redesign or fundamentally change the process system
When common cause variation prevents a process from meeting specs, the entire system must be changed — reacting to individual parts makes the problem worse, not better.
Question 7: In statistical thinking, the term 'noise' refers to:
- Loud machinery interfering with measurements
- Special cause variation that disrupts production
- Common cause variation inherent to the process (Correct answer)
- Customer complaints about product consistency
Correct answer: Common cause variation inherent to the process
In statistical terms, 'noise' describes common cause variation — the natural, unavoidable random variation always present in any process.
Lean Six Sigma Yellow Belt Certification Statistical Thinking and Variation 1
What are the two main types of process variation recognized in Six Sigma?