Statistical analysis of linear and nonlinear correlation of the Arrhenius equation constants

Engineers must often use correlations that were developed before statistical analysis and verification of the correlation became a routine procedure. In this paper, we use modern statistical techniques to compare the traditional linear regression technique with the modern nonlinear regression as applied to the Arrhenius equation. The objective of the comparison is to determine whether there are basic flaws with the technique used in the past and whether these flaws may render the constants published in the literature untrustworthy. It is concluded that linear regression, when applied to the Arrhenius expression, is in principle not inferior to nonlinear regression and if the relative error in the data is distributed normally, it can even be superior. Nevertheless, if insufficient data were used for calculation of the constants and/or the experimental data were interpolated or smoothed, the accuracy of the published correlation is unpredictable. (C) 1997 Elsevier Science S.A.