BIOSTAT 216
Mathematical Methods for Biostatistics
Biostatistics · 4 units · Graduate courses (200-299)
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.
Requisites
Official UCLA wording
Requisites: Mathematics 31A, 31B, 33A.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.





