BIOSTAT M257Computational 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.
When it runs
Not on the schedule for any of Fall 2025 through Spring 2027. UCLA publishes only that window, so this does not mean the course is gone — check the official listing.
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
- STATS 100CLinear Models
- MATH 170SIntroduction to Probability and Statistics 2: Statistics
- STATS 100BIntroduction to Mathematical Statistics
3 direct requisites. Showing 17 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.
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.