Statistical Thinking and Variation Flashcards
7 cards from real Lean Six Sigma Yellow 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 Statistical Thinking and Variation flashcards as text
What are the two main types of process variation recognized in Six Sigma?
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).
Which of the following is an example of special cause variation?
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.
Walter Shewhart's primary contribution to statistical thinking was developing a method to:
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.
A process that exhibits only common cause variation is described as:
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.
Statistical thinking in Six Sigma is best described as:
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.
What is the appropriate response when a process displays only common cause variation but does not meet customer specifications?
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.
In statistical thinking, the term 'noise' refers to:
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.