Aplicación de la estadística robusta en la identificación de valores “OUTLIERS” en análisis de residuos de clorpirifos en maní. programa elaborado en Hp-Basic utilizando la calculadora gráfica HP Prime

In the present work, robust statistics have been applied for the identification of "outliers" values in the determination of the recovered factor in the analysis of chlorpyrifos residues in peanut by gas chromatography with detector ECD. For this, a program was developed in the HPBASIC language, based on robust statistics and specifically on the Huber algorithm and which was edited in the latest generation HP PRIME Graphing Calculator. e program was executed by entering the data obtained from the results of the evaluation of the recovery factor for the method of analysis of chlorpyrifos in an internal peanut reference sample, obtaining as a result an estimate of the parameters of the population and the identification of 3 "Outliers" is program was validated with a reference made in Excel by the Committee of Analytical Methods of the Royal Society of Chemistry, observing that the deviation of the parameters of the population (m,s) were lower than the iterative precision, which indicates that there were no significant differences between the two programs. On the other hand, these results were compared with those obtained by the classic tests of Dixon and Grubbs, concluding that the Huber method is the most sensitive. e least sensitive is the Dixon test, given that its application did not detect any outlier, whereas the Grubbs test identified the two smallest values.