Test of the Randomness of Residuals and Detection of Potential Outliers for the Buchanan-3-phase Model Used in the Fitting of the Effect of nZVI/Pd and SiO2-nZVI/Pd Nanoparticles on the Growth of P. putida

Authors

  • Garba Uba Department of Science Laboratory Technology, College of Science and Technology, Jigawa State Polytechnic, Dutse, PMB 7040, Nigeria.
  • Murtala Ya'u Department of Biochemistry, Faculty of Basic Medical Sciences, College of Health Sciences, Bayero University Kano, Kano, PMB 3001- Nigeria.
  • Ibrahim A. Allamin Department of Microbiology, Faculty of Science, University of Maiduguri P.M.B 1069 Maiduguri, Nigeria.

DOI:

https://doi.org/10.54987/jebat.v5i1.680

Keywords:

Wald–Wolfowitz runs test, Buchanan-3-phase model, Nanoparticles, P. putida, Grubb’s test

Abstract

Lots of studies do not perform statistical diagnostics on the nonlinear model that was used, therefore the data may not be random. Because these systems rely on random data, this is a necessity for all parametric statistical assessment procedures. When the diagnostic tests show that the residuals constitute a pattern, there are several options for treatment, including switching to a new model or performing a nonparametric analysis. These treatments, as well as others like them, should solve the issue. We employ the Wald-Wolfowitz runs test as a statistical diagnosis tool to determine whether or not the randomization conditions have been met. Because it was critical to examine the randomness of the residual for the Buchanan-3-phase model used in the fitting of the effect of nZVI/Pd and SiO2-nZVI/Pd nanoparticles on the growth of Pseudomonas putida, it was decided to conduct this study using the Wald-Wolfowitz runs test. The run test indicated that there were 7 total runs, whereas 7.15 runs were predicted based on the randomization assumption. This shows that the residual series contains suitable runs. Because the p-value was greater than 0.05, the null hypothesis was not rejected; this means that there is no persuasive evidence of the residuals' non-randomness; rather, the residuals represent noise. This implies that no extra effort is required to discover potential outliers. Because there was no outlier, the data did not need to be reanalyzed as a result of Grubb's test results. Overall, the residual analysis indicates that the Buchanan-3-phase model used in the fitting of the effect of nZVI/Pd and SiO2-nZVI/Pd nanoparticles on the growth of P. putida was adequate.

References

Augustin JC, Brouillaud-Delattre A, Rosso L, Carlier V. Significance of inoculum size in the lag time of Listeria monocytogenes. Appl Environ Microbiol. 2000;66(4):1706-10.

Arroyo-López FN, Bautista-Gallego J, Durán-Quintana MC, Garrido-Fernández A. Modelling the inhibition of sorbic and benzoic acids on a native yeast cocktail from table olives. Food Microbiol. 2008 Jun 1;25(4):566-74.

Fujikawa H. Development of a new logistic model for microbial growth in foods. Biocontrol Sci. 2010;15(3):75-80.

Mathias SP, Rosenthal A, Gaspar A, Aragão GMF, Slongo-Marcusi A. Prediction of acid lactic-bacteria growth in Turkey ham processed by high hydrostatic pressure. Braz J Microbiol. 2013;44(1):23-8.

Ye K, Wang H, Zhang X, Jiang Y, Xu X, Zhou G. Development and validation of a molecular predictive model to describe the growth of Listeria monocytogenes in vacuum-packaged chilled pork. Food Control. 2013;32(1):246-54.

Altuntas S, Cinar A, Altuntas V. Modelling of Listeria monocytogenes growth and survival in presence of royal jelly, a promising anti-biofilm agent. J Food Nutr Res. 2020 Jan;59(1):7-15.

Motulsky HJ, Ransnas LA. Fitting curves to data using nonlinear regression: a practical and nonmathematical review. FASEB J Off Publ Fed Am Soc Exp Biol. 1987;1(5):365-74.

D'Agostino RB. Tests for the normal distribution. In: Goodness-of-fit techniques. Routledge; 2017. p. 367-420.

Grubbs F. Procedures for detecting outlying observations in samples. Technometrics. 1969;11(1):1-21.

Motulsky HJ, Brown RE. Detecting outliers when fitting data with nonlinear regression - A new method based on robust nonlinear regression and the false discovery rate. BMC Bioinformatics. 2006;7.

Lazaridis NK, Asouhidou DD. Kinetics of sorptive removal of chromium(VI) from aqueous solutions by calcined Mg-Al-CO3 hydrotalcite. Water Res. 2003 Jul 1;37(12):2875-82.

Sabullah MK, Shukor MS, Masdor NA, Shamaan NA, Shukor MY. Test of randomness of residuals for the Buchanan-three-phase model used in the fitting the growth of Moraxella sp. B on monobromoacetic acid (MBA). Bull Environ Sci Manag. 2015;3(1):13-5.

Uba G, Mansur A, Manogaran M, Shukor MY. Runs Test for the Residuals of The Morgan-Mercer-Flodin (MMF) Model Used for Modelling the Total Number of Covid-19 Cases for Brazil. Bull Environ Sci Sustain Manag. 2021 Jul 31;5(1):7-11.

Draper NR, Smith H. Applied Regression Analysis. Wiley, New York; 1981.

López S, Prieto M, Dijkstra J, Dhanoa MS, France J. Statistical evaluation of mathematical models for microbial growth. Int J Food Microbiol. 2004;96(3):289-300.

Barnett V, Lewis T. Outliers in Statistical Data. 3rd ed. Chichester?; New York: Wiley; 1994. 604 p.

Rosner B. Fundamentals of biostatistics. 7th ed. Boston: Brooks/Cole; 2011.

Tietjen GL, Moore RH. Some Grubbs-Type Statistics for the Detection of Several Outliers. Technometrics. 1972;14(3):583-97.

Horn R, Stewart AJ, Jackson KV, Dryburgh EL, Medina-Torres CE, Bertin FR. Clinical implications of using adrenocorticotropic hormone diagnostic cutoffs or reference intervals to diagnose pituitary pars intermedia dysfunction in mature horses. J Vet Intern Med. 2021;35(1):560-70.

Shukor MY. Outlier and Normality Testing of the Residuals from the Carreau-Yasuda Model in Fitting the Rheological Behavior of the Non-Newtonian fluid TF2N. Bioremediation Sci Technol Res. 2021 Jul 31;9(1):20-6.

Uba G, Zandam ND, Mansur A, Shukor MY. Outlier and Normality Testing of the Residuals for the Morgan-Mercer-Flodin (MMF) Model Used for Modelling the Total Number of COVID-19 Cases for Brazil. Bioremediation Sci Technol Res. 2021 Jul 31;9(1):13-9.

Li J. A Practical $O(N^2)$O(N2) Outlier Removal Method for Correspondence-Based Point Cloud Registration. IEEE Trans Pattern Anal Mach Intell. 2022 Aug;44(8):3926-39.

Huitema BE, McKean JW, Zhao J. The runs test for autocorrelated errors: unacceptable properties. J Educ Behav Stat. 1996;21(4):390-404.

Halmi MIE, Shukor MS, Johari WLW, Shukor MY. Evaluation of several mathematical models for fitting the growth of the algae Dunaliella tertiolecta. Asian J Plant Biol. 2014;2(1):1-6.

Gunasekaran B, Shukor MS, Masdor NA, Shamaan NA, Shukor MY. Test of randomness of residuals for the Buchanan-three-phase model used in the fitting the growth of Paracoccus sp. SKG on acetonitrile. J Environ Bioremediation Toxicol. 2015;3(1):12-4.

Cataldo S, Gianguzza A, Merli M, Muratore N, Piazzese D, Turco Liveri ML. Experimental and robust modeling approach for lead(II) uptake by alginate gel beads: Influence of the ionic strength and medium composition. J Colloid Interface Sci. 2014 Nov 15;434:77-88.

Umar G. Test of the Randomness of Residuals for the Pseudo-1st Order Kinetic Modelling of Adsorption of the Brominated Flame Retardant 4-bromodiphenyl Ether onto Biochar-immobilized Sphingomonas sp. Bioremediation Sci Technol Res. 2021 Jul 31;9(1):27-31.

Cooper SM, Baker JS, Eaton ZE, Matthews N. A simple multistage field test for the prediction of anaerobic capacity in female games players. Br J Sports Med. 2004;38(6):784-9.

Worthington AC, Higgs H. Efficiency in the Australian stock market, 1875-2006: A note on extreme long-run random walk behaviour. Appl Econ Lett. 2009;16(3):301-6.

Abu GA, Abachi PT, Oloja-Ojabo ED. Long-run relationship between agricultural crop prices and supply response in Benue State, Nigeria: 1990-2010. Eur J Soc Sci. 2011;24(4):565-75.

Burns RD, Hannon JC, Brusseau TA, Eisenman PA, Shultz BB, Saint-Maurice PF, et al. Development of an aerobic capacity prediction model from one-mile run/walk performance in adolescents aged 13-16 years. J Sports Sci. 2016;34(1):18-26.

Gardiner SK, Mansberger SL. Effect of restricting perimetry testing algorithms to reliable sensitivities on test-retest variability. Invest Ophthalmol Vis Sci. 2016;57(13):5631-6.

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Published

2022-08-05

How to Cite

Uba, G., Ya’u, M. ., & Allamin, I. A. (2022). Test of the Randomness of Residuals and Detection of Potential Outliers for the Buchanan-3-phase Model Used in the Fitting of the Effect of nZVI/Pd and SiO2-nZVI/Pd Nanoparticles on the Growth of P. putida. Journal of Environmental Bioremediation and Toxicology, 5(1), 45–49. https://doi.org/10.54987/jebat.v5i1.680

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