Computational Methods for Biostatistical Research

BIOMATH M257 - Computational Methods for Biostatistical Research

<p>(Formerly numbered 257.) (Same as Biomathematics M257.) Lecture, three hours; discussion, one hour. Requisites: course 250A or Statistics 100C, Mathematics 115A. 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.</p>

Biostatistics

The school aims to build health and equity, and to drive positive change for all people. The school acts on this mission through initiatives in three core areas: education, discovery, and service.

Jonathan and Karin Fielding School of Public Health

Biostatistics encompasses the methodology and theory of statistics as applied to problems in the life and health sciences.

General Catalog

Computational Methods for Biostatistical Research

BIOSTAT M257

4 units