Encyclopaedia of Statistical Theory describes the fundamental concepts and application probability and statistics. By bringing together modern probability theory with the more practical application of statistics it bridges the gap between theory and practice. This encyclopaedia demonstrates the usefulness of geometric methods in probability theory and mathematical statistics, and shows close relationships between these disciplines and convex analysis. Deep facts and statements from the theory of convex sets are discussed with their applications to various questions arising in probability theory, mathematical statistics, and the theory of stochastic processes. This encyclopaedia takes advantage of modern technology, to facilitate statistical reasoning as well as the understanding and interpretation of statistical results. Encyclopaedia of Statistical theory covers the basics of descriptive statistics, including the most frequently used inferential tests for research design with two conditions (t-tests and their non-parametric of both descriptive and inferential statistics are discussed and illustrated in situations that are close to most students' own experience. Students with a background limited to basic algebra will be able to complete the necessary mathematical calculations. This encyclopaedia ids essential reading for practicing engineers who need a sound background knowledge of statistical and probabilistic concepts and methods of analysis for their everyday work. It is also a useful guide for graduate engineering students.