The fundamentals of mformatlonal statlstlcs are explamed wth regard to theu Importance for analytical chenustry Informational statlstlcs, hke robust statlstlcal techniques, are resistant agamst uncertamtles concernmg the data, such as outhers or divergences from the normal drstnbutlon
Usmg a new mformatlonal function, namely mformatlonal energy, the null hypothesis was tested to decide whether a certain factor has a significant effect on the results
Keywora% Analysis of variance, Informational statistics
In any experunent two or more methods (laboratories) yield generally more or less different results, because analytlcal determmatlons may be influenced by basic factors (quahtatlve or quantltatrve) that control the condltlons of experiment and also by random factors
It IS the objective of analysis of variance (ANOVA) to investigate the several kmds of factors, operatmg simultaneously, and to decide which are important and to esttmate their effects ANOVA assumes the addltlvlty of variances of random variables due to the effects of mdependent factors It 1s used to break down the total variance into its components, i e , into a sum of several distinct components, each corresponding to a source of variance
The F-tests that are subsequently made are determined from the ratios of these respective components The F ratio can then be compared with tabulated F values using the degrees of Correspondence to C Sirbu, Department of Analytical Chemistry,