A procedure whereby one or two mutually exclusive and exhaustive statements about a population is concluded. Information from a sample is used to infer something about a population from which the…

Question

Options

• AHypothesis Testing
• BDesign of Experiment
• CBeta Risk
• DBenchmarking

• A
  90% (27)
• B
  7% (2)
• C
  3% (1)

Explanation

Hypothesis Testing (A) fits perfectly because it is literally defined as the procedure of choosing between two mutually exclusive and exhaustive statements about a population (null vs. alternative hypothesis) using sample data to draw inferences - matching every word in the question.

Why the distractors are wrong:

• B (Design of Experiment) is about planning how to collect data (controlling variables, randomization) - it precedes inference, it doesn't make probabilistic statements about a population.
• C (Beta Risk) is a specific error concept within hypothesis testing (the probability of a Type II error - failing to reject a false null) - a component, not the procedure itself.
• D (Benchmarking) is a performance comparison practice (measuring against a standard or competitor) - it has nothing to do with statistical inference from samples.

Memory tip: Remember the two key phrases - "mutually exclusive and exhaustive statements" (null/alternative hypotheses cover all possibilities and can't both be true) and "sample to population" (inference direction). Any time you see both of those together, it's Hypothesis Testing.

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