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- W2115409304 abstract "Breeders need powerful and simply understood statistical methods when analyzing disease reaction data. However, many disease reaction experiments result in data which do not adhere to the classical analysis of variance (ANOVA) assumptions of normality, homogeneity variance and a correctly specified model. Nonparametric statistical methods which require fewer assumptions than classical ANOVA, are applied to data from several disease reaction experiments. It is concluded that nonparametric methods are easily understood, can be productively applied to plant disease experiments and many times result in improved chances for detecting differences between treatments." @default.
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- W2115409304 date "1994-05-01" @default.
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- W2115409304 title "999 STATISTICAL ANALYSIS OF DISEASE REACTION DATA USING NONPARAMETRIC METHODS" @default.
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- W2115409304 doi "https://doi.org/10.21273/hortsci.29.5.572e" @default.
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