Analysis of variance is the name given to a collection of statistical methods originally used to analyze data obtained from experiments. The experiments make us of a quantitative dependent variable, also known as a metric variable or an interval or ratio variable, and one or more qualitative independent variables, also known as categorical or nominal variables. These analysis methods grew out of agricultural experiments in the beginning of the twentieth century, and the great English statistician Sir Ronald Fisher developed many of these methods. As an example, the dependent variable could be the yield in kilos of wheat from different plots of land and the independent variable could by types of fertilizers used on the plots of land.
Experimental Design
The way an experiment is run affects the particular analysis of variance method used for the analysis of the data. Experiments are designed according to different plans, and the choice of the design of the experiment affects which...
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Hinkelmann K, Kempthorne O (2008) Design and analysis of experiments, I and II, 2nd edn. Wiley, New York
Iversen GR, Norpoth H (1987) Analysis of variance, 2nd edn. Sage Baverly Hills, CA
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© 2011 Springer-Verlag Berlin Heidelberg
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Iversen, G.R. (2011). Analysis of Variance. In: Lovric, M. (eds) International Encyclopedia of Statistical Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04898-2_117
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DOI: https://doi.org/10.1007/978-3-642-04898-2_117
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