Random sampling plans are based on which of the following assumption?

Question

Options

• AThe process is unstable.
• BThe data are accurate.
• CA specific dependency model has been selected.
• DEvery item has an equal chance of being selected.

• A
  12% (4)
• B
  3% (1)
• C
  9% (3)
• D
  76% (26)

Explanation

Random sampling plans rest on the foundational principle that every item in the population has an equal and independent probability of being selected - this equal-chance assumption is what makes the sample statistically representative and free from selection bias. Option A is wrong because random sampling assumes a stable process; an unstable process would make sampling results unreliable and uninterpretable. Option B is a general quality requirement, not a defining assumption of random sampling itself - data accuracy matters broadly, but it doesn't describe how items are chosen. Option C describes systematic or model-based sampling (e.g., stratified or cluster sampling), which explicitly departs from pure random selection by imposing structure.

Memory tip: Think of a lottery - every ticket has the same odds. Random sampling = lottery logic. If anything tilts the odds (instability, bias, a model), it's no longer purely random.

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