Abstract
In studying methods for the analysis of quantitative data, we first focused on problems involving a single sample of numbers and then turned to a comparative analysis of two different samples. Now we are ready for the analysis of several samples.
Keywords
- Simultaneous Confidence Level
- True Average Response
- Single Factor ANOVA
- Expected Mean Squares
- ANOVA Table
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- 1.
This is referred to as an “unrestricted” model. An alternative “restricted” model requires that Σ i G ij = 0 (so the G ij ’s are no longer independent). Expected mean squares and F ratios appropriate for testing certain hypotheses depend on the choice of model. MINITAB’s default option gives output for the unrestricted model.
Bibliography
Miller, Rupert, Beyond ANOVA: The Basics of Applied Statistics, Wiley, New York, 1986. An excellent source of information about assumption checking and alternative methods of analysis
Montgomery, Douglas, Design and Analysis of Experiments (7th ed.), Wiley, New York, 2009. An up-to-date presentation of ANOVA models and methodology.
Kutner, Michael, Christopher Nachtsheim, John Neter, and William Li, Applied Linear Statistical Models (5th ed.), McGraw-Hill, New York, NY, 2005. The second half of this book contains a well-presented survey of ANOVA; the level is comparable to that of the present text, but the discussion is more comprehensive, making the book an excellent reference
Ott, R. Lyman, and Michael Longnecker, An Introduction to Statistical Methods and Data Analysis (6th ed.), Cengage, Belmont, CA, 2010. Includes several chapters on ANOVA methodology that can profitably be read by students desiring a nonmathematical exposition; there is a good chapter on various multiple comparison methods
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© 2012 Springer Science+Business Media, LLC
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Devore, J.L., Berk, K.N. (2012). The Analysis of Variance. In: Modern Mathematical Statistics with Applications. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0391-3_11
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