In modern electric power networks with fast evolving operational conditions, assessing the impact of contingencies is becoming more and more crucial. Contingencies of interest can be roughly classified into nodal power disturbances and line faults. Despite their higher relevance, line contingencies have been significantly less investigated analytically than nodal disturbances. The main reason for this is that nodal power disturbances are additive perturbations, while line contingencies are multiplicative perturbations, which modify the interaction graph of the network. They are therefore significantly more challenging to tackle analytically. Here, we assess the direct impact of a line loss by means of the maximal Rate of Change of Frequency (RoCoF) incurred by the system. We show that the RoCoF depends on the initial power flow on the removed line and on the inertia of the bus where it is measured. We further derive analytical expressions for the expectation and variance of the maximal RoCoF, in terms of the expectations and variances of the power profile in the case of power systems with power uncertainties. This gives analytical tools to identify the most critical lines in an electric power grid.Electrical networks can be subjected to many types of disturbances, such as small to medium fluctuations of the power injections and consumptions due to intermittent energy sources, larger power disturbances such as power plant outages, or the breakdown of an electrical line. There are various measures of the impact of such disturbances. For instance, one may consider the time the system requires to settle back to a synchronous state, or the magnitude of the excursion of some quantities, such as voltage angles or frequency, away from their desired values. In this work, we investigate the effect of a line loss on the Rate of Change of Frequency (RoCoF), which is the largest time derivative of the voltage frequencies. It is a measure of the severity of a perturbation that is standardly used in the operation of electric power grids. In practice, the current operating state of the system is not known. We therefore derive statistical properties of the Ro-CoF after a line loss for cases when the exact operating state of the system is uncertain.