Tsallis statistics, which is based on a non-additive entropy characterized by an index q, is a very useful tool in physics and statistical mechanics. This paper presents an application of Tsallis statistics in reliability analysis. We first show that the q-gamma and incomplete q-gamma functions are q-generalized. Then, three commonly used statistical distributions in reliability analysis are introduced in Tsallis statistics, and the corresponding reliability characteristics including the reliability function, hazard function, cumulative hazard function and mean time to failure are investigated. In addition, we study the statistical inference based on censored reliability data. Specifically, we investigate the point and interval estimation of the model parameters of the q-exponential distribution based on the maximum likelihood method. Simulated and real-life datasets are used to illustrate the methodologies discussed in this paper. Finally, some concluding remarks are provided.