Normality, Grubb’s and Runs Tests for the von Bertalanffy model used in the fitting of the growth of Bacillus cereus strain wwcp1 on malachite green dye (Journal of Environmental Bioremediation and Toxicology, 2022)
When diagnostic tests show that the residuals form a pattern, there are a few treatment alternatives to choose from. Two of these choices are running a nonparametric analysis and switching to a different model. In this study, the Wald-Wolfowitz runs test is utilized as a statistical diagnosis approach to determine whether or not the randomization criteria have been met. The Wald-Wolfowitz runs test was chosen as the best method to use for this research since it was necessary to examine the randomness of the residual for the von Bertalanffy model used in the fitting of the growth of Bacillus cereus strain wwcp1 on malachite green dye. The observations indicated that the residual series had an adequate number of runs; this was the outcome. The runs test discovered four runs, despite the fact that the randomization assumption predicted thirteen runs. This implies that the runs in the residual collection are only marginally meaningful. The fact that the p-value was less than 0.05 indicates that the null hypothesis is rejected; this implies that the residuals include convincing evidence of non-randomness. Furthermore, this demonstrates the need of looking at potential outliers. However, the test for the lack of an outlier does not demand reanalysis of the data, as indicated by Grubb's test findings. To resolve this discrepancy, either a different model needs to be used or more data needs to be added.
Keywords: Wald–Wolfowitz runs test; Residual; von Bertalanffy model; outlier; Grubb’s test