A Chi-Square Methodology Applied in Deviations Control of Project Plan to support the RIMAM model

This paper describes a Hybrid Chi-Squared methodology of Project Plan deviations identification, including those for multiple deviations in a Project Plan system. The sampling methodology was used to analyze similarity, together with a statistical optimization methodology for Chi-Squared, to improve the existing methodology used to forecast data in the Project Plan phase. The created sampling methodology was utilized for learning activities of Project Plan, in order to detect deviations. This Chi-Squared methodology was employed by empirical results. The results have shown that the selection strategy identify better forecasting approach between two different proposals, aiming to provide the forecasting process of Project Plan, presenting better precisions based on the diagnose deviations detection, within this Chi-Squared methodology.