UNIVARTIATE, MULTIVARIATE AND PERMUTATIONAL ANALYSIS OF VARIANCE METHODS FOR FORESTRY DATA BY USING R
Keywords:
Anova, ancova, forestry data, manova, peranova, permanova, R languageAbstract
Analysis of Variance has been widely used in the analysis of forestry research data. They have contributed to a very common question in forest science: are factors affect results of experiments? Analysis of variance (ANOVA) can help researchers to analyze the effect of one or more factors on experimental results. In the meanwhile, ANCOVA besides examining the effects of factors, they also help to check the effect of covariance as well as the relationship between factors and covariance. To make more objective and accurate conclusions, MANOVA should be applied, because MANOVA is able to analyze the effect of factors on experimental results based on various continuous variables. Permutational univariate and multivariate analysis of variance (PERANOVA and PERMANOVA) are new analysis tools. These tools do not require any assumptions. Because of this, scientists can apply them in various fields of forest science. To support and implement PERANOVA and PERMANOVA, the R language should be implemented. The reason is that powerful statistical analysis softwares like SPSS, Stata or Sas is difficult or impossible to conduct these contents.
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