BIOSTAT M257
Computational Methods for Biostatistical Research
Biostatistics · 4 units · Graduate courses (200-299)
(Same as Biomathematics M257.) Preparation for quantitative research in statistics and data sciences. Numerical analysis and hands-on computing techniques for handling big data. Numerical analysis topics include computer arithmetic, solving linear equations, Cholesky factorization, QR factorization, regression computations, eigenvalue problems, iterative solvers, numerical optimization, and design and analysis of statistical simulation experiments. Computing techniques include basics of R programming, reproducible research using R and RStudio, collaborative research, parallel computing, and cloud computing. No prior knowledge of R assumed.
S/U or letter grading.
Requisites
Official UCLA wording
Requisites: course 250A or Statistics 100C, Mathematics 115A.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
BIOSTAT M257
- BIOSTAT 250ALinear Statistical Models
- MATH 115ALinear Algebra
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.





