Lecture, four hours. Requisites: Mathematics 31A, 31B, 33A. Designed and required for incoming first-year MS and PhD students. Introduction to specialized topics in advanced calculus, linear algebra, and scientific computing that are pertinent for subsequent courses in MS and PhD Biostatistic curriculum. Offers more in-depth understanding of mathematical rigor used in subsequent required courses such as Biostatistics 200B, 200C, 202A, 202B, and 202C. Emphasis on interplay between mathematical methods and scientific computing within R statistics computing environment. Offers detailed training on numerical algorithms used in linear algebra and probabilistic simulations commonly used by statisticians. Examination of several of the most common R functions used in statistical modeling such as regression analysis and random effects models. S/U or letter grading.