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An accessible and up-to-date introduction to the tools needed to address modern inference problems in engineering and data science, ideal for students taking graduate courses on statistical inference/detection and estimation, this textbook : -Presents the core principles of statistical inference in a unified manner by gathering together tools - particularly those involving large sample sizes - from across the current literature ; - Is mathematically accessible, providing many examples to illustrate the concepts explained ; - Contains a wealth of illustrations to emphasize the key features of the theory, the implications of the assumptions made, and the subtleties that arise when applying the theory ; - Offers extended material exploring advanced topics ; - Includes numerous application examples, connecting the theory with practical applications ; and - Provides end-of-chapter exercises, including computer-based problems.