The objective of this work is to determine how much information the methodology ROR can give when having a series whose selfcorrelograms are a white noise. It was used the variable of the monthly fallen rain in Caibarién, Cuba, in the period 1977-2014. By using modeling ROR, it has been obtained information for the future projection of data series of errors by modeling ARIMA, as this type of modeling opens an important and promising way for the series that behave as white noise, by giving new information for the series and its behavior. The model explains the 8.7 % of variance, with errors of 44.6 mm. The errors tendency is the increase around 0.004 mm, although it is not statistically significant, the errors depend on the errors 1 month behind. All the work was carried out with the help of the statistical package of Social Sciences (SPSS) Version 13.
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