Data coming basically from GO/NO-GO, pass/fail determinations of whether units conform to standards.

Question

Options

• AAttribute Data
• BDiscrete Data
• CVariable Data
• DSample Size

• A
  89% (40)
• B
  2% (1)
• C
  2% (1)
• D
  7% (3)

Explanation

Attribute Data (A) is correct because GO/NO-GO and pass/fail inspections classify units into categories - conforming or non-conforming - without measuring a continuous value. Attribute data counts or categorizes; it answers "did it pass?" not "how much?"

Why the distractors are wrong:

• B (Discrete Data) is a broader statistical term for countable whole-number values; while attribute data is discrete, "discrete data" doesn't specifically describe the GO/NO-GO classification context the question is testing.
• C (Variable Data) is the opposite - it involves actual measurements on a continuous scale (length, weight, temperature), not binary pass/fail judgments.
• D (Sample Size) is not a data type at all; it refers to how many units are selected for inspection.

Memory tip: Think of "attribute" as a label you assign - a unit either has the attribute (pass) or it doesn't (fail). If you're measuring how much, that's variable; if you're judging yes or no, that's attribute.

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