We demonstrate how the surrogate process approximation (SPA) method can be used to compute both the potential of mean force (PMF) along a reaction coordinate and the associated diffusion coefficient using a relatively small (10-20) set of bidirectional non-equilibrium trajectories coming from a complex system. Our method provides confidence bands which take the variability of the initial condition, continuous nature of the work paths, and thermal fluctuations into account. Maximum likelihood type methods are used to estimate a stochastic differential equation (SDE) approximating the dynamics and assist in these computations. For each observed time series, we estimate a new SDE resulting in a collection of SPA models. The physical significance of the collection of SPA models is discussed and methods for exploiting information in this population of models are suggested. Molecular dynamics(MD) simulations of potassium ion dynamics inside a gramicidin A channel are used to demonstrate the methodology, although SPA type modeling has also proven useful in analyzing single-molecule experimental time series [J. Phys. Chem. B,ﾠ113, 118 (2009)].