BIOSTAT 241Spatial Modeling and Data Analysis for Health Sciences
Biostatistics · 4 units · Graduate courses (200-299)
Introduction of various methods for exploring, modeling, and analyzing spatially referenced datasets, with emphasis on environmental/natural sciences and public health. Statistical theory and foundations for carrying out principled and scientifically rigorous inference on spatially referenced datasets and computational methods and algorithms for executing statistical modeling in practice. Practical examples and applications demonstrated using open-source statistical software environment R and datasets from diverse fields, such as public health, environmental health, natural sciences, and economics.
Letter grading.
When it runs
- Fall 2025
- 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
Requisites: courses 200A, 200B, 202A, 202B.
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 241
- BIOSTAT 200AMethods in Biostatistics A
- BIOSTAT 200BMethods in Biostatistics B
- BIOSTAT 202AMathematical Statistics A
- BIOSTAT 202BMathematical Statistics B
4 direct requisites. The whole upstream is here — 6 courses over 2 levels. 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.