Biostatistics (Graduate Group) Graduate Studies

Group Office

4118 Mathematical Sciences Building; Biostatistics Graduate Group
Advising Resources. Graduate Advisors

Faculty

Danielle Harvey, Ph.D. (Public Health Sciences), Chairperson of the Group
Faculty Directory

About

The Graduate Group in Biostatistics offers M.S. and Ph.D. programs in Biostatistics.

Biostatistics (BST)

BST 222 — Biostatistics: Survival Analysis (4 units)

Course Description: Incomplete data; life tables; nonparametric methods; parametric methods; accelerated failure time models; proportional hazards models; partial likelihood; advanced topics.

Prerequisite(s): STA 131C.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Cross Listing: STA 222.
  • Grade Mode: Letter.

BST 223 — Biostatistics: Generalized Linear Models (4 units)

Course Description: Likelihood and linear regression; generalized linear model; Binomial regression; case-control studies; dose-response and bioassay; Poisson regression; Gamma regression; quasi-likelihood models; estimating equations; multivariate GLMs.

Prerequisite(s): STA 131C.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Cross Listing: STA 223.
  • Grade Mode: Letter.

BST 224 — Analysis of Longitudinal Data (4 units)

Course Description: Standard and advanced methodology, theory, algorithms, and applications relevant for analysis of repeated measurements and longitudinal data in biostatistical and statistical settings.

Prerequisite(s): (BST 222 or STA 222); (BST 223 or STA 223); STA 232B; or consent of instructor.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Cross Listing: STA 224.
  • Grade Mode: Letter.

BST 225 — Clinical Trials (4 units)

Course Description: Basic statistical principles of clinical designs, including bias, randomization, blocking, and masking. Practical applications of widely-used designs, including dose-finding, comparative and cluster randomization designs. Advanced statistical procedures for analysis of data collected in clinical trials.

Prerequisite(s): BST 223 or STA 223; or consent of instructor.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Cross Listing: STA 225.
  • Grade Mode: Letter.

BST 226 — Statistical Methods for Bioinformatics (4 units)

Course Description: Standard and advanced statistical methodology, theory, algorithms, and applications relevant to the analysis of -omics data.

Prerequisite(s): BST 131C or consent of instructor; data analysis experience recommended.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Cross Listing: STA 226.
  • Grade Mode: Letter.

BST 227 — Machine Learning in Genomics (4 units)

Course Description: Emerging problems in molecular biology and current machine learning-based solutions to those problem. How deep learning, kernel methods, graphical models, feature selection, non-parametric models and other techniques can be applied to application areas such as gene editing, gene network inference and analysis, chromatin state inference, cancer genomics and single cell genomics.

Prerequisite(s): STA 208 or ECS 171; or consent of instructor.

  • Learning Activities: Lecture/Discussion 3 hour(s), Project.
  • Grade Mode: Letter.

BST 252 — Advanced Topics in Biostatistics (4 units)

Course Description: Biostatistical methods and models selected from the following: genetics, bioinformatics and genomics;longitudinal or functional data; clinical trials and experimental design; analysis of environmental data; dose-response, nutrition and toxicology; survival analysis; observational studies and epidemiology; computer-intensive or Bayesian methods in biostatistics.

Prerequisite(s): BST 222; BST 223.

  • Learning Activities: Lecture 3 hour(s), Discussion/Laboratory 1 hour(s).
  • Repeat Credit: May be repeated when topic differs with consent of advisor.
  • Cross Listing: STA 252.
  • Grade Mode: Letter.

BST 290 — Seminar in Biostatistics (1 unit)

Course Description: Seminar on advanced topics in the field of biostatistics. Presented by members of the Biostatistics Graduate Group and other guest speakers.

  • Learning Activities: Seminar 1 hour(s).
  • Enrollment Restriction(s): Restricted to graduate standing.
  • Repeat Credit: May be repeated 12 time(s).
  • Grade Mode: Satisfactory/Unsatisfactory only.

BST 298 — Directed Group Study (1-5 units)

Course Description: Special topics in Biostatistics appropriate for group study at the graduate level.

  • Learning Activities: Variable 3-15 hour(s).
  • Repeat Credit: May be repeated.
  • Grade Mode: Letter.

BST 299 — Special Study for Biostat Graduate Students (1-12 units)

Course Description: Special topics in Biostatistics appropriate for directed individual study on advanced topics not otherwise covered in the Biostatistics curriculum.

  • Learning Activities: Variable 3-36 hour(s).
  • Repeat Credit: May be repeated.
  • Grade Mode: Satisfactory/Unsatisfactory only.

BST 299D — Dissertation Research (1-12 units)

Course Description: Research in Biostatistics under the supervision of major professor.

Prerequisite(s): Consent of instructor; advancement to Candidacy for Ph.D.

  • Learning Activities: Variable 3-36 hour(s).
  • Repeat Credit: May be repeated.
  • Grade Mode: Satisfactory/Unsatisfactory only.