BIOSTAT 200AMethods in Biostatistics A
Biostatistics · 4 units · Graduate courses (200-299)
First course in biostatistical methods intended for graduate students in biostatistics to prepare students pursuing careers as practicing biostatisticians. Prior knowledge of probability or statistics not assumed. Students should have working knowledge of calculus and be very comfortable with mathematical and algebraic reasoning. Introduction to basic concepts in analysis, presentation of data, and statistical aspects of design of studies. Special emphasis is given to application of statistical methods to public health, medical, biological, and health sciences. Interpretation and communication of statistical findings is stressed. Focus on methodology, applications, and concepts rather than mathematical statistics or probability theory.
S/U or letter grading.
When it runs
- Fall 2025
- Fall 2026
Scheduled, not typical — from UCLA’s Schedule of Classes, which publishes Fall 2025 through Spring 2027 and nothing before it.
Requisites
UCLA lists no requisites for this course.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
BIOSTAT 200A1 more beyond
- BIOMATH M207BApplied Genetic Modeling
- BIOSTAT 213Introduction to Computational Methods in Biostatistics
- HUM GEN M207BApplied Genetic Modeling
- BIOSTAT M234Applied Bayesian Inference
- BIOSTAT M236Longitudinal Data
- BIOSTAT 202CTheory of Bayesian Statistics
- ENV HLT 210Quantitative Exposure Assessment
- BIOSTAT 211ATopics in Applied Regression
- BIOSTAT 211BTopics in Applied Regression
- EPIDEM 245Lifestyle Intervention: Study Design and Data Analysis
- BIOSTAT 214Finite Population Sampling
- EPIDEM 205Methods for Analyzing Non-Randomized and Quasi-Experimental Studies
- BIOSTAT 230Statistical Graphics
- BIOSTAT 231Statistical Power and Sample Size Methods for Health Research
- HLT POL 237CIssues in Health Services Methodologies
- BIOSTAT 241Spatial Modeling and Data Analysis for Health Sciences
- BIOSTAT 250BLinear Statistical Models
- BIOSTAT 250CMultivariate Biostatistics
- EPIDEM 206Systems Science Modeling and Simulation in Epidemiology
- BIOSTAT 274Topics in Statistical Machine Learning
- BIOSTAT 402APrinciples of Biostatistical Consulting
- BIOSTAT 402BBiostatistical Consulting
- BIOSTAT 595Effective Integration of Biostatistical Concepts in Public Health Research
- EPIDEM 207Reproducibility in Epidemiologic Research
17 courses list this as a requisite. Showing 28 courses over 2 levels; the branches marked with a count carry on past it. Every course here opens its own tree.