Balanced ANOVA

Balanced ANOVA is a statistical test used to determine whether or not different groups have different means. Analysis of variance testing (ANOVA) is used to test the differences between means for statistical significance. An ANOVA analysis is typically applied to a set of data in which sample sizes are kept equal for each treatment combination. Balanced ANOVA tests are often done with computer software due to the complexity of mathematical calculations. It does not work well in experiments in which observations are missing or extra observations are present.

A one-way ANOVA test checks for significance for one factor only, while a two-way ANOVA test analyzes the effects of two factors simultaneously. Two-way ANOVA tests are the most useful when the replicate examples are equal, or "balanced."

ANOVA is used in finance in several different ways, such as to forecast the movements of security prices by first determining which factors influence stock fluctuations. Factor investing focuses on both macroeconomics and investing style, and this quantitative analysis can provide valuable insight into the behavior of a security or market index under various conditions. For example, it could show how much of a security's rise or fall is due to changes in interest rates. A t-test and f-test are used to analyze the results of an analysis of variance test to determine which variables are of statistical significance.