Analysis+of+Variance

Analysis of Variance (ANOVA) (Multivariate Methods) (GWU EMSE-271)
Index | Topics (Logical Lectures) | Lectures | Problems | Readings | Nomenclature | Concepts

ANOVA Analysis | ANOVA Table Formats | Constrasts | 2-Way | 2K Factorial | Assumptions **(** One-Way | Two-Way ) | MANOVA AND MANCOVA

Uses: "Whether a particular factor or factors … have significant impacts on the dependent variable." Lattin p420

"In statistics, **analysis of variance (ANOVA)** is a collection of statistical models, and their associated procedures, in which the observed variance is partitioned into components due to different explanatory variables. In its simplest form ANOVA gives a statistical test of whether the means of several groups are all equal, and therefore generalizes Student's two-sample //t//-test to more than two groups." - [|Wikipedia]
 * ANOVA is a special case of regression analysis. One thing that makes ANOVA special is that the factors are usually coded to discrete values instead of being continuous. - Lattin, page 15
 * "ANOVA is used overwhelmingly for analyzing data collected from experimental methods." " Number of applications is practically uncountable. " - Lattin, p 387
 * Important to do ANOVA instead of multiple two-sample t-test (on all possible pairs) because of "a considerable distortion in the type I error." - EMSE 271, Fall 2009, slide 285.
 * Factors are called treatments. - Lattin and EMSE 271
 * ANOVA tests for variance means (F-test) ( not a Chi-squared test variance hypothesis test)

Read Lattin Learning Summary, pages 420-421 for more.

Variations: ANCOVA, MANOVA, MANCOVA


 * Sources:**
 * Analysis of variance. (2009, November 24). In //Wikipedia, The Free Encyclopedia//. Retrieved 16:30, December 2, 2009, from []
 * Analyzing Multivariate Data, by James Lattin, Douglas Carroll and Green ([|Amazon])
 * EMSE 271, Fall 2009