The purpose of a full factorial design is to:

Question

Options

• Aprovide information on the effects of main factors
• Bprovide information on the effects of interactions
• Cif possible, remove the effects of lurking
• Dall of the above
• Enone of the above

• A
  3% (1)
• C
  3% (1)
• D
  93% (27)

Explanation

A full factorial design tests every possible combination of factor levels, which simultaneously accomplishes all three goals listed: it estimates main effects (A), detects interaction effects between factors (B), and by systematically controlling all factors in the experiment, it helps account for lurking variables that might otherwise confound results (C) - making D the only complete answer.

Options A, B, and C are each individually true but incomplete on their own; choosing any single one misrepresents the full power of the design. Option E is clearly wrong since the design does have well-defined purposes.

Memory tip: Think of "full factorial" as "full coverage" - you're running every combination, so you get everything: main effects, interactions, and control over confounds. If it's not full, it's a fractional factorial, and you start losing information (usually interactions).

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