Final answer:
MANOVA, or Multivariate Analysis of Variance, is a statistical test used to compare population means on several dependent variables across different groups, extending the one-way ANOVA which is used for a single dependent variable.
Step-by-step explanation:
The MANOVA test, or Multivariate Analysis of Variance, is an extension of the ANOVA (Analysis of Variance) method. Whereas ANOVA is used to analyze differences among group means when there is one dependent variable, MANOVA is used when there are multiple dependent variables. It evaluates whether the population means on several variables are different among groups. In a MANOVA test, the independent variables are categorical, and the dependent variables are metric. It is much like one-way ANOVA but it looks at multiple responses simultaneously. The assumptions for conducting a MANOVA are similar to those required for ANOVA, which include normally distributed populations, equal variances, and independent random samples. To explain the use of MANOVA, consider a consumer comparing several car models based on multiple characteristics such as gas mileage, cost of insurance, and reliability. MANOVA would allow the consumer to assess whether there are statistical differences in these characteristics across the different models simultaneously, rather than evaluating each characteristic separately with multiple ANOVAs.