BIOSTAT 200BMethods in Biostatistics B
Biostatistics · 4 units · Graduate courses (200-299)
Designed for students pursuing graduate degrees in biostatistics. Theory and practice of linear regression analysis and analysis of variance (ANOVA).
S/U or letter grading.
When it runs
- Winter 2026
- Winter 2027
Scheduled, not typical — from UCLA’s Schedule of Classes, which publishes Fall 2025 through Spring 2027 and nothing before it.
Requisites
Official UCLA wording
Preparation: linear algebra. Requisite: course 200A.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
- · could not read "linear algebra" (no course number found)
- · no course reference could be read from this requisite
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 200B
- BIOSTAT 200AMethods in Biostatistics A
1 direct requisite. The whole upstream is here — 1 course over 1 level. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
BIOSTAT 200B7 more beyond
- BIOSTAT 202CTheory of Bayesian Statistics
- BIOSTAT 211ATopics in Applied Regression
- BIOSTAT 211BTopics in Applied Regression
- EPIDEM 245Lifestyle Intervention: Study Design and Data Analysis
- BIOMATH M207BApplied Genetic Modeling
- BIOSTAT 213Introduction to Computational Methods in Biostatistics
- BIOSTAT 214Finite Population Sampling
- EPIDEM 205Methods for Analyzing Non-Randomized and Quasi-Experimental Studies
- BIOSTAT 231Statistical Power and Sample Size Methods for Health Research
- BIOSTAT M234Applied Bayesian Inference
- HLT POL 237CIssues in Health Services Methodologies
- BIOSTAT M236Longitudinal Data
- BIOSTAT M237Applied Genetic Modeling
- HUM GEN M207BApplied Genetic Modeling
- BIOSTAT M238Methodology of Clinical Trials
- BIOSTAT 241Spatial Modeling and Data Analysis for Health Sciences
- BIOMATH M234Applied Bayesian Inference
22 courses list this as a requisite. Showing 17 courses over 2 levels; the branches marked with a count carry on past it. Every course here opens its own tree.