Anova Assumptions Violated. If the X or Y populations from which data to be analyzed by analysis of covariance ANCOVA were sampled violate one or more of the ANCOVA assumptions the results of the analysis may be incorrect or misleading. Independence of samples Pseudoreplication Early Mid Late Down slope Up slope Pseudoreplicates because they are not spatially independent Cannot prove there are no confounding factors Environmental gradient Topographical gradient Difficult to measure the variance between signal and the variance within noise.
Describe the assumptions for use of analysis of variance ANOVA and the tests to checking these assumptions normality heterogeneity of variances outliers. If the populations from which data to be analyzed by a one-way analysis of variance ANOVA were sampled violate one or more of the one-way ANOVA test assumptions the results of the analysis may be incorrect or misleading. Feb 27 2013 The assumption of homogeneity of variance is an assumption of the independent samples t-test and ANOVA stating that all comparison groups have the same variance.
Unfortunately it is not easy or possible to figure out how far off the p-value actually is.
In a nutshell ANOVA is used to evaluate differences between at least three group means to determine whether there is a statistically significant difference somewhere. In regression models the assumption comes in to play with regards to residuals aka errors. The responses for each factor level have a normal population distribution. This section reviews both graphical and inferential methods for evaluating the assumptions for the 1-way ANOVA omnibus F test and the use of the pooled within-group error for contrasts and multiple comparisions.
