ANOVA Algorithm

(Redirected from analysis of variance)
Jump to navigation Jump to search

An ANOVA algorithm is a population mean difference analysis algorithm by partitioning the data into components attributable to different sources of variation.



  • (Wikipedia, 2013) ⇒
    • Analysis of variance (ANOVA) is a collection of statistical models used to analyze the differences between group means and their associated procedures (such as "variation" among and between groups). In ANOVA setting, the observed variance in a particular variable is partitioned into components attributable to different sources of variation. In its simplest form, ANOVA provides a statistical test of whether or not the means of several groups are equal, and therefore generalizes t-test to more than two groups. Doing multiple two-sample t-tests would result in an increased chance of committing a type I error. For this reason, ANOVAs are useful in comparing (testing) three or more means (groups or variables) for statistical significance.




  • (Starbird, 2006) ⇒ Michael Starbird. (2006). “Meaning from Data: Statistics Made Clear.” The Teaching Company
    • QUOTE: analysis of variance (ANOVA): A procedure of statistical analysis by which differences in means of two or more groups can be assessed after eliminating variance that is due to other factors.