Individual variability in parameter settings can have an impact on accuracy when simulating the electrical behavior of the heart. The direct effect of increases or decreases in conduction velocity values on the spread of activation is well known, but what is considerably less understood is the impact of unknown variability in conduction velocity. We aim to test the impact of inevitable uncertainty in conduction velocities on the output of simulations of cardiac propagation, given three different stimulus locations on the left ventricular free wall. To understand the impact of physiological variability in conduction velocity on simulations of cardiac activation, we generated detailed maps of the variability in simulations of propagation by implementing bi-ventricular activation simulations; to quantify these effects, we employed uncertainty quantification techniques based on polynomial chaos expansion. Polynomial chaos expansion allows for efficient exploration with reduced computational demand by utilizing an emulator function that approximates the underlying forward model. The computed statistical parameters included mean, standard deviation, and skewness. Our results suggest that conduction velocity within healthy physiological ranges plays a small role in the activation times across all stimulation locations. However, areas of strong positive skew in the activation times are present on the epicardial surface during mid-myocardial stimulation. We observed low levels of variation in activation times near the earliest activation sites, while higher variation was observed toward the termination sites. Areas of increased skewness during mid-myocardial stimulation showed that the majority of activation times were below the mean; suggesting highly nonlinear impacts of conduction velocity on propagation on the left ventricular epicardial surface. Overall, our results suggest that the conduction velocities assigned in simulations of myocardial propagation play a relatively small role, depending on the specific objectives and research or clinical goals and whether or not the tissue is healthy or affected by underlying conditions.