Many methods are used in reliability engineering for both quantitative and qualitative analysis, among which statistical methods are undoubtedly among the most important. This chapter presents key statistical concepts and methods that are essential for reliability analysis. Statistics, as a fundamental branch of mathematics, is well developed with mature theories. However, applying statistical methods to reliability problems without a proper understanding of their fundamentals and limitations can be risky. Misconceptions and misuse of statistical methods are common in state-of-the-art applications of reliability engineering. This hchapter introduces statistics from a practical perspective for reliability. It begins with parameter estimation, including discussions on confidence interval derivation, consistency, and asymptotic normality. It then addresses parameter bias, methods for goodness-of-fit test, and approaches for approximating cumulative distribution functions.