Abstract
In Chapter 4 we showed how to compare the variances of two samples to determine whether the corresponding data sets appeared to represent the same population. We calculated a variance estimate for each sample, and then compared their ratio to the F distribution. In this chapter, we extend that concept to the analysis of variance (ANOVA) of several (more than two) samples. In Figure 1–3, our diagnostic tree directs us to ANOVA when we want to analyze relationships among factors involved in an experimental design.
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© 2001 Robert P. Trueblood and John N. Lovett, Jr.
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Trueblood, R.P., Lovett, J.N. (2001). Analysis of Experimental Designs. In: Data Mining and Statistical Analysis Using SQL. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-0855-6_7
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DOI: https://doi.org/10.1007/978-1-4302-0855-6_7
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-893115-54-5
Online ISBN: 978-1-4302-0855-6
eBook Packages: Springer Book Archive