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Inspection of the residuals confirmed that the data met the general assumptions of multiple regression models (e.g. normality, linearity, homoscedasticity).
To test whether the data met the assumption of collinearity, VIF scores were calculated, with values between 1.1 and 1.5, indicating that multicollinearity was not a concern.
According to Field (2009) and Hooper, Coughlan, and Mullen (2008), the data met guidelines for univariate normality and multivariate normality, and there were no multivariate outliers.
Where the data met the assumptions of normality and homogeneity of variances, t-tests were used for comparisons between clearcut and control sites, and partial harvest treatments were compared with ANOVA.
The data met the assumption of normality and homogeneity of variance.
The data met the assumptions for the various statistical tests.
Similar(25)
The U.S. Food and Drug Administration FDAA) will approve a product only if the data meets certain statistical criteria, so position is very important in a trial's success.
Statistical tests require that the data meet several specific assumptions that should be checked before making any inference about the values of parameters.
The data meet the assumptions of the tests.
Relevance denotes how well the data meet the information needs of the user.
CIHD counts are "suppressed" when the data meets the criteria for confidentiality constraints.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com