In this paper, we investigate the use of the Contribution to the Sample Mean plot (CSM plot) as a
graphical tool for sensitivity analysis (SA) of computational models. We first provide an exact formula
that links, for each uncertain model input Xj , the CSM plot Cj (·) with the first-order variance-based
sensitivity index Sj .We then build a new estimate for Sj using polynomial regression of the CSM plot.
This estimation procedure allows the computation of Sj from given data, without any SA-specific
design of experiment. Numerical results show that this new Sj estimate is efficient for large sample
sizes, but that at small sample sizes it does not compare well with other Sj estimation technique
based on given data, such as the EASI method