The ability to accurately predict available bandwidth of an end-to-end path is of importance for improving quality of services for end users. For instance, end users can receive high quality video if senders can select to stream video data on an end-to-end path with available bandwidth that fits the required transmission rate. Modeling available bandwidth of an end-to-end path as a stochastic process is one of the approaches that can be used to predict the future available bandwidth of the path. The effectiveness of this approach depends on how well the chosen stochastic process can model the available bandwidth. The result of our analysis on the data published by Stanford Linear Accelerator Center (SLAC) indicates that Brownian Motion processes are not good for modeling available bandwidth of an end-to-end path.