Shape memory alloy(SMA) has "super elasticity", that is, it can recover original shape after deformation and unloading due to stress, and dissipate energy in this process. It has broad application prospect in seismic control of buildings and bridge vibration. The model parameters of SMA are often determined through optimization and treated as deterministic for dynamic analysis of structures with SMA based devices. In this study, the modified Metropolis-Hasting algorithm-DRAM algorithm, which is a combination of delay rejection and adaptive sampling, is utilized to characterize the uncertainties in modified Graesser & Cozzarelli SMA model parameters. A series of SMA bars with the same geometric size and heat treatment were tested under cyclic loads. The Markov Chain Monte Carlo (MCMC) method is applied to analyze the uncertainties of SMA in terms of model parameters and energy dissipation capacity. The analysis provide insight into the underlying mathematical form of a model, suggest simplifications or modifications and begin to indicate the relative significance of individual parameters, based on a limited set of experimental data. Besides, research shows thatthe energy dissipation of the SMA bar could have up to a relative error of 20% and 10% corresponding to the CDF of 15% and 85%.