For experiments with two independent variables, which analysis is typically used?

For experiments with two independent variables, which analysis is typically used?

• A. Two-Way ANOVA
• B. One-Way ANOVA
• C. MANOVA
• D. ANCOVA

Answer: (A)

Two-way ANOVA is used when you have two independent variables and a continuous outcome. It tests the main effect of each factor on the dependent variable and whether there is an interaction between the two factors—that is, whether the effect of one factor depends on the level of the other. This makes it ideal for factorial designs with two factors because it lets you see both separate influences and combined effects in one analysis. If there is only one factor, you’d use a one-way ANOVA. If you’re analyzing multiple dependent variables at once, you’d consider MANOVA. If you need to adjust for covariates, ANCOVA is appropriate. For data where measurements are taken repeatedly, you’d use a repeated-measures or mixed-model approach, but the core idea for two factors is captured by two-way ANOVA.

Two-way ANOVA is used when you have two independent variables and a continuous outcome. It tests the main effect of each factor on the dependent variable and whether there is an interaction between the two factors—that is, whether the effect of one factor depends on the level of the other. This makes it ideal for factorial designs with two factors because it lets you see both separate influences and combined effects in one analysis. If there is only one factor, you’d use a one-way ANOVA. If you’re analyzing multiple dependent variables at once, you’d consider MANOVA. If you need to adjust for covariates, ANCOVA is appropriate. For data where measurements are taken repeatedly, you’d use a repeated-measures or mixed-model approach, but the core idea for two factors is captured by two-way ANOVA.