Statistical Inference I

Catalog description

The course is the first of a sequence in the theory of statistical interference and probability. The first part of the course covers probability theory; discrete, continuous, and exponential distribution functions; moment generating functions; and differentiation. The latter part of the course covers joint and marginal distributions and concepts of random samples. Students taking this course need to have completed at least one year of college calculus. Students will develop a project that synthesizes the course learning objectives through an applied course project. The course focuses on the theoretical underpinnings of biostatistics and improving understanding of statistical application and problem solving approaches.