MANOVA, or Multivariate Analysis of Variance, is a statistical test used to determine if there are any differences in the means of multiple dependent variables across different groups. It extends the ANOVA framework to accommodate multiple dependent variables, allowing researchers to understand the effect of independent variables on a vector of dependent variables simultaneously while accounting for the correlation between them.

MANOVA

Multivariate Analysis of Variance (MANOVA) is a statistical test used to determine if there are any differences between independent groups on more than one continuous dependent variable. It extends the ANOVA by considering multiple dependent variables simultaneously, accounting for the potential correlations between them and providing a more comprehensive understanding of the data's structure.

Multivariate Analysis of Variance

A statistical test is a method used to determine if there is a significant effect or relationship present in a dataset, often by comparing observed data against a null hypothesis. The choice of test depends on the data type, distribution, and the specific research question being addressed.

statistical test

differences in the means

multiple dependent variables

different groups

ANOVA framework

Independent variables are factors or conditions that are manipulated or categorized to determine their effect on dependent variables in an experiment or study. They are essential for establishing cause-and-effect relationships and are crucial in hypothesis testing and experimental design.

independent variables

Dependent variables are the outcomes or responses that researchers measure in an experiment to assess the effect of independent variables. They provide insight into causal relationships by reflecting changes that occur due to manipulations in the experimental setup.

Relevant Degrees

Log in to see lessons