MANOVA is appropriate when there are multiple dependent variables. True or false?

MANOVA is appropriate when there are multiple dependent variables. True or false?

• A. True
• B. False
• C. Only when one dependent variable is measured
• D. Only for nonparametric data

Answer: (A)

MANOVA is designed for situations with more than one dependent variable measured on the same subjects, and it tests whether the groups differ on the combination of outcomes. Running separate tests for each dependent variable can miss the way variables relate to one another, and MANOVA accounts for that by evaluating the multivariate mean vector across groups. Because of this, it’s appropriate whenever you have two or more dependent variables that may be correlated. It’s not about a single outcome, and it’s a parametric method rather than a nonparametric one.

MANOVA is designed for situations with more than one dependent variable measured on the same subjects, and it tests whether the groups differ on the combination of outcomes. Running separate tests for each dependent variable can miss the way variables relate to one another, and MANOVA accounts for that by evaluating the multivariate mean vector across groups. Because of this, it’s appropriate whenever you have two or more dependent variables that may be correlated. It’s not about a single outcome, and it’s a parametric method rather than a nonparametric one.