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Automotive electrical/electronic (E/E) architectures need to be evaluated and selected based on the estimated performance of the functions deployed on them before the details of these functions are known. End-to-end delays of controls must be estimated using incomplete and aggregate information on the computation and communication load for ECUs and buses. We describe the use of statistical analysis to compute the probability distribution of Controller Area Network (CAN) message response times when only partial information is available about the functionality and architecture of a vehicle. We provide results compared to simulations as well as trace data. These results demonstrate that our statistical inference can be used for predicting the distribution of the response time of a CAN message, once its priority has been assigned, from limited information such as the bus utilization of higher priority messages.