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Erschienen in:
2014 | OriginalPaper | Buchkapitel
4. Inference Using Analysis of Variance for Comparing Multiple Means
verfasst von : Hang Lee
Erschienen in: Foundations of Applied Statistical Methods
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Abstract
This chapter discusses single-factor analysis of variance (ANOVA) which is mainly applied to compare three or more independent means. The words “single factor” refer to that the means are compared across levels of a “single” classification variable (i.e., classification of means by a single categorical variable). The classification variable is called independent variable or factor (thus, the method is also called single-factor ANOVA) and the outcome variable of which the means are compared is called dependent variable. This method requires certain assumptions: (1) the dependent variable values are the observations sampled from a normal distribution and (2) the population variances are equal (homoscedasticity) across the levels of the independent variable.