Course Description
This course is designed to survey topics and tools needed for an undergraduate statistics major to begin to develop a broad and thorough working knowledge of modern computational techniques for statistical inferences. Statistical methods and the algorithms used to facilitate their computations are motivated by building logical foundations for statistical reasoning. Algorithms surveyed can broadly be categorized as either optimization based or sampling based. Rather than focusing on learning standard software packages for implementing common statistical routines, all codes will be written from scratch using the R programming language (or any other high-level language of the students' choosing). Emphasis is placed on developing a practical understanding of how and why existing methods work, and when to apply a particular method. Some programming proficiency is assumed.