In this chapter we consider parameter estimation which we regard as an application of Bayesian statistics to the problem of data fusion. We first consider curve fitting which we regard as a problem in fusing multiple sensor observations. Maximum a posteriori, maximum likelihood and minimum mean square error solutions are compared and we determine under what conditions these solutions are equal. Finally we consider the linear Gaussian model and the problem of change point detection.