Analysis of Variance (ANOVA) is a statistical inference method utilized to test hypotheses about mean differences among three or more groups defined by categorical independent variables within the domain of experimental design and multivariate statistics. The core principle relies on partitioning total variability in a dependent variable into components attributable to specific factors, random error, and their interactions to determine if observed group means differ significantly under null hypothesis testing frameworks. This concept serves as a foundational theoretical mechanism for evaluating factorial effects and assessing model fit prior to the execution of complex experimental designs such as full factorial analyses.
Prerequisite chain context: requires Main Effects in Design of Experiments.