Unmanned aerial vehicles are safety-critical systems. A failure in the system behavior may lead to hazards and serious consequences. The assessment of the system dependability characteristics that include safety and reliability early in the design phase is a beneficial task that helps to avoid expensive redesign and iterations in later design phases. Unmanned aerial vehicles typically comprise several independent components that communicate and share data via a network. Adequate timing is crucial for proper system behavior. However, the timing is affected by various system faults, e. g., network induced delays, which typically have a stochastic nature. The focus of this paper is on the effective model-based application of the previously published method for the analysis of timing errors to a realistic case study model of a quadcopter. The holistic solution proposed in this paper integrates the SysML modeling and annotating approach, the automated transformation of the SysML model to a Stochastic Petri Net, and the identification, formalization, and analysis of timing properties. The case study model is annotated with the timing parameters recorded from a real-world system. The results of the conducted sensitivity analysis reveal the effects of parameter changes in the annotated timing properties. These quantitative results may be used as input for the error propagation analysis, allow the assessment of the system dependability and enable to compare different design options concerning the occurrence of timing errors.