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Analysis of variance
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===Textbook analysis using a normal distribution=== The analysis of variance can be presented in terms of a [[linear model]], which makes the following assumptions about the [[probability distribution]] of the responses:<ref>{{cite book |title = Statistical Methods | last1 = Snedecor | first1 = George W. | last2 = Cochran | first2 = William G. | year = 1967 | edition = 6th | page = 321 }}</ref><ref>Cochran & Cox (1992, p 48)</ref><ref>Howell (2002, p 323)</ref><ref> {{cite book | last1 = Anderson | first1 = David R. | last2 = Sweeney | first2 = Dennis J. | last3 = Williams | first3 = Thomas A. | title = Statistics for business and economics | publisher = West Pub. Co | location = Minneapolis/St. Paul | year = 1996 | edition = 6th| isbn = 978-0-314-06378-6 | pages = 452β453}} </ref> * [[Statistical independence|Independence]] of observations β this is an assumption of the model that simplifies the statistical analysis. * [[normal distribution|Normality]] β the distributions of the [[Residual (statistics)|residuals]] are [[Normal distribution|normal]]. * Equality (or "homogeneity") of variances, called [[homoscedasticity]]βthe variance of data in groups should be the same. The separate assumptions of the textbook model imply that the [[errors and residuals in statistics|errors]] are independently, identically, and normally distributed for fixed effects models, that is, that the errors (<math>\varepsilon</math>) are independent and <math display="block">\varepsilon \thicksim N(0, \sigma^2).</math>
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