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ISEB-PM1 · Question #516

What is the name of the statistical method that helps identify which factors may influence specific variables of a product or process under development or in production?

The correct answer is B. Design of experiments. Design of Experiments (DoE) is the statistical method specifically designed to systematically identify which input factors influence output variables in a product or process - it does this by deliberately varying factors and measuring their effects, making it the only choice…

Quality Management

Question

What is the name of the statistical method that helps identify which factors may influence specific variables of a product or process under development or in production?

Options

  • AFailure modes and effects analysis
  • BDesign of experiments
  • CQuality checklist
  • DRisk analysis

How the community answered

(41 responses)
  • A
    2% (1)
  • B
    78% (32)
  • C
    7% (3)
  • D
    12% (5)

Explanation

Design of Experiments (DoE) is the statistical method specifically designed to systematically identify which input factors influence output variables in a product or process - it does this by deliberately varying factors and measuring their effects, making it the only choice here that is both statistical and focused on factor-variable relationships.

Why the distractors are wrong:

  • A. Failure Modes and Effects Analysis (FMEA) identifies what can go wrong and the consequences, not which factors statistically influence variables.
  • C. Quality Checklist is a simple verification tool - it confirms steps were completed, not causal relationships.
  • D. Risk Analysis evaluates probability and impact of risks broadly; it doesn't isolate which factors drive specific process variables.

Memory tip: Think of DoE as "running controlled experiments like a scientist" - you design tests to see what factors move the needle on your outcome. The word "experiments" is the giveaway: only DoE is an experimental (statistical) method among the four choices.

Topics

#design of experiments#statistical methods#quality planning#process variables

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