(untitled) (Asian Journal of Plant Biology, 2014)
Mathematical modeling of physical, chemical or biological data could help the investigator to explain a phenomenon observed based on physical, chemical or biological mechanisms. The model could also be used to predict or forecast future behavior, simulate a hypothetical event or input and design better experiments. Previously, we demonstrated that the Baranyi-Roberts growth kinetics is the best model using the ordinary least squares method for the growth of the algae Dunaliella tertiolecta compared to other models such as modified logistic, modified Gompertz, modified Richards, modified Schnute, Baranyi-Roberts, Von Bertalanffy, Huang and the Buchanan three-phase linear model. The ordinary least squares method relies heavily on several important assumptions such as residuals conformation to normal distribution, does not have outliers, is truly random, of equal variance (homoscedastic) and does not show autocorrelation. If all of these assumptions are satisfied, the test is said to be robust. In this work we perform statistical diagnosis test for the adequacy of the model to satisfy these requirements.