Multivariate statistical analysis approach to investigate the thermodynamic quantities of the benign alternative fuel Scientific paper

Abstract

In order to extract meaningful interpretation from the large data and provide their value to the application areas, chemical data analysis has become a serious challenge in the development and applications of new protocols, tech­nique and methodologies for the mathematical modelling communities and other data science societies. Therefore, in the present work a rapid and robust box-and-whisker plot and multivariate principal component statistical tech­niques (PCA) are being proposed for the evaluations of the thermodynamic molecular properties data of the benign fuel structures. We observed that, the box-and-whisker plot technique successfully explored all of the thermo­chem­ical molecular properties precisely, and described symmetrical distribution of the data along the median values with respect to the rise in temperature. More­over, applying the PCA technique, the score-plots of PCs diagnosed the pecu­liar molecular properties variations after a certain peak of temperature with descendant variation in the statistical parameters. Furthermore, PCA para­meters not only segregated the thermodynamic properties of propanol and but­anol but also, their variations with the temperature. Thus, we concluded that, Box-whis­ker and PCA statistical techniques are robust and rapid method for the assess­ment and evaluation of the large molecular thermodynamic quantities data.