The autocorrelation coefficient test does not take into consideration the degree

As a result, all values of ρ that are close to 1 are signs of inadequate fitting of models. The autocorrelation coefficient (ρ) is a statistical measure, which implies that the independent value of ρ does not supply adequate information on the subject of ‘goodness of fit.’ It is imperative for the statistic to be slotted into a test that determines the goodness of fit for it to yield meaningful information.

Several studies have looked into the ρ statistic as a valuable instrument for evaluating the goodness of fit following the tallying of biokinetic models with information on bioassays. These studies have brought to light the fact that the ρ test enables the unprejudiced detection of partiality in the succession of residuals following the fitting of a poor archetype to a series of data.

The autocorrelation coefficient test does not take into consideration the degree of miscalculations that are made by the evaluator. The chi-square (χ²) test, on the other hand, is susceptible to the slightest inaccuracies made by the evaluator. Another point worth noting is that it is impossible to employ the ρ test in instances where a given data array contains less than four values (Puncher 2007).