Inference Using Analysis of Variance (ANOVA) for Comparing Multiple Means

Hang Lee
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Hang Lee: Department of Medicine, Harvard Medical School, Massachusetts General Hospital Biostatistics Center

Chapter Chapter 4 in Foundations of Applied Statistical Methods, 2023, pp 85-97 from Springer

Abstract: Abstract This chapter discusses single-factor analysis of variance (ANOVA), which is mainly applied to compare three or more independent means. The term “single factor” refers 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 the independent variable or factor (thus, the method is also called single-factor ANOVA), and the outcome variable whose means are compared is called the 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 (homoskedasticity) across the levels of the independent variable (Fig. 4.1).

Date: 2023
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DOI: 10.1007/978-3-031-42296-6_4

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