BIOSTAT 200C
Methods in Biostatistics C
Biostatistics · 4 units · Graduate courses (200-299)
Preferred preparation: courses 200A, 200B, and previous coursework in linear algebra. Designed for students pursuing graduate degrees in biostatistics. Generalized linear models, description, and analysis of discrete data with applications to public health. Students are trained to identify different types of discrete data; use statistical software package STATA to manage, summarize, and analyze data; use appropriate statistical techniques for analyzing public health data using generalized linear models; apply generalized estimating equations for analyzing longitudinal data; and write formal statistical report of data analysis for public health researcher.
S/U or letter grading.
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 200C
- BIOSTAT M232Statistical Analysis of Incomplete Data
- BIOSTAT 233Statistical Issues in Global Health
- BIOMATH M232Statistical Analysis of Incomplete Data
- BIOSTAT M235Causal Inference
- BIOSTAT 245Advanced Seminar: Biostatistics
- PSYCTRY M232Causal Inference
- BIOSTAT 246Doctoral Students Seminar
- BIOSTAT 250BLinear Statistical Models
- BIOSTAT 250CMultivariate Biostatistics
- BIOSTAT 273Machine Learning
9 courses list this as a requisite. The whole downstream is here — 10 courses over 2 levels. Every course here opens its own tree.