In the domain of Experimental Dynamic Substructuring, precision in the experimental measurements has an important role and tend to affect the final results drastically if left unconsidered. This study aims to propagate potential errors to the interface reduction point obtained using the Virtual Point Transformation algorithm (VPT) and later to a substructure coupling obtained using the Frequency-Based Substructuring (FBS). This paper will analyse three types of errors: position and orientation measurement errors of sensors, and random noise-based errors in the measured Frequency Response Functions(FRFs). The uncertainty quantification is performed using a computationally efficient, first-order second moment (FOSM) method and later validated using Monte-Carlo simulations. The method is applied to a structure, whose FRFs have been obtained numerically. The results indicate that the orientation measurement error of the sensors is the most significant followed by FRF-based random error and position measurement error respectively.