Which statement best describes a related factorial design?

Which statement best describes a related factorial design?

• A. a between-subjects design where each predictor is manipulated in a separate group.
• B. an experimental design incorporating two or more predictors all manipulated using the same participants.
• C. a design with two dependent variables.
• D. a correlational design with multiple variables.

Answer: (B)

A factorial design looks at more than one independent variable at once, and a related (within-subjects) factorial design means the same participants experience every combination of the factors. This setup lets you test not only main effects of each factor but also how the factors interact, while reducing error due to individual differences because the same people are measured across all conditions. The statement that two or more predictors are manipulated using the same participants best describes this idea, because it captures both the presence of multiple factors and the within-subjects nature of the design. The other statements don’t fit. Describing a between-subjects design where each predictor is manipulated in a separate group misses the core idea of a factorial design where all factors are presented within the same participants. A design with two dependent variables speaks to the measurement side rather than how the factors are manipulated. And a correlational design with multiple variables is nonexperimental, so it doesn’t describe a factorial experimental setup at all.

A factorial design looks at more than one independent variable at once, and a related (within-subjects) factorial design means the same participants experience every combination of the factors. This setup lets you test not only main effects of each factor but also how the factors interact, while reducing error due to individual differences because the same people are measured across all conditions.

The statement that two or more predictors are manipulated using the same participants best describes this idea, because it captures both the presence of multiple factors and the within-subjects nature of the design.

The other statements don’t fit. Describing a between-subjects design where each predictor is manipulated in a separate group misses the core idea of a factorial design where all factors are presented within the same participants. A design with two dependent variables speaks to the measurement side rather than how the factors are manipulated. And a correlational design with multiple variables is nonexperimental, so it doesn’t describe a factorial experimental setup at all.