1. A computer-implemented method for statistical data learning under privacy constraints, the method comprising: receiving, by a processor, a plurality of pieces of uncertain statistical information relating to a statistical object from a plurality of telematics units, wherein each piece of uncertain statistical information corresponds to an uncertainty variable having been applied to a corresponding piece of actual statistical information by a respective telematics unit from which the piece of uncertain statistical information was received, wherein the uncertainty variable corresponds to noise added by the respective telematics unit according to a common function having a predetermined mean implemented by each of the plurality of telematics units; and aggregating, by the processor, the plurality of pieces of uncertain statistical information to generate an estimated value corresponding to the statistical object.