Biostatistics for Public Health Research
Hands-on experience using statistical tools to answer real-world questions. Students will design and implement a short survey and analyze their results. Emphasis on analysis of actual survey data using statistical software. Statistical topics include numerical/graphical summaries, measures of association, and hypothesis testing. Focus is on interpretation, not calculation. GEN foundation math and quantitative reasoning or data analysis course.
Prerequisites: None
Learn more
|
Honors Biostatistics for Public Health Research
Hands-on experience using statistical tools to answer real-world questions. Students will design and implement a short survey and analyze their results. Emphasis on analysis of actual survey data using statistical software. Statistical topics include numerical/graphical summaries, measures of association, and hypothesis testing. Focus is on interpretation, not calculation. GEN foundation math and quantitative reasoning or data analysis course.
Prerequisites: Honors standing or permission of instructor.
Learn more
|
PUBHBIO 3193
Credits: 1‐6
Individual Studies in Biostatistics
Individual studies in Biostatistics focusing on applied topics.
Prerequisites: Permission of instructor.
Learn more
|
Introduction to Genomic Data Analysis
Provides an in‐depth analysis of a specific question to which genomic methods are applied. Intersperses experimental methods and statistical analysis of biological data. Some experience with programming is recommended.
Prerequisites: Jr. standing or above, and Math 1151 or 1156, STAT 2450 or 2480, and Biology 1113 or MolGen 5660, or Grad standing; or permission of instructor.
Learn more
|
Applied Biostatistics I
Theory and application of basic statistical concepts for design of studies in health sciences, integrated with statistical
software applications.
Prerequisites: Grad standing.
Learn more
|
Applied Biostatistics II
A second course in applied biostatistical methods with an emphasis on regression methods commonly used in the health sciences. The focus is on linear regression and ANOVA. Integrated with use of computer statistical packages.
Prerequisites: Grade of B‐ or above in PUBHBIO 6210 or PUBHLTH 6001 or permission of instructor.
Learn more
|
Regression Methods for the Health Sciences
A second course in regression modeling for public health, including models for binary outcomes, count outcomes, survival/censored outcomes, and data collected from complex survey designs.
Prerequisites: PUBHBIO 6211, or permission of instructor.
Learn more
|
Ethics in Biostatistics
The course examines ethical challenges related to research design, data collection, data integrity and stewardship, data analysis and interpretation, and data reporting in the conduct of public health and biomedical research. Through presentation of historical and current case studies we discuss ethical concerns commonly faced by biostatisticians and provide tools to address future quandaries.
Prerequisites: Prerequisites: Enrollment in MPH-Biostatistics specialization, or MS-Biostatistics specialization, or Interdisciplinary PhD in Biostatistics, or permission of instructor
Learn more
|
Introduction to SAS for Public Health Students
Introduction to programming using SAS software to accomplish
public health data management and analysis.
Prerequisites: Grad standing in PUBHLTH, or permission of instructor. Not open to students with credit
for STAT 5740, or 6740.
Learn more
|
PUBHBIO 7193
Credits: 1‐6
Individual Studies in Biostatistics
Independent study in Biostatistics.
Prerequisites: Permission of instructor.
Learn more
|
PUBHBIO 7194
Credits: 1‐3
Group Studies in Biostatistics
Group studies in biostatistical methods. Format will include
lectures, readings, presentations and discussions in an area of special interest to students and faculty.
Prerequisites: Permission of instructor.
Learn more
|
Design and Analysis of Clinical Trials
Design, monitoring, and analysis of clinical trials; includes protocol development, randomization schemes, sample size
methods, and ethical issues.
Prerequisites: Stat 5301, or PUBHBIO 6210, PUBHLTH 6001 or equiv; or permission of instructor.
Learn more
|
Applied Generalized Linear Models in Public Health
Introduce students to generalized linear models (GLMs) for categorical and discrete data and their application in clinical and public health research.
Prerequisites: PUBHBIO 6211 or permission of instructor
Learn more
|
Survey Sampling Methods
Sampling from finite populations, simple random, stratified, systematic and cluster sampling design, ratio and regression
estimates, non‐sampling errors, models.
Prerequisites: PUBHBIO 6211, or Stat 5301 or equiv.
Learn more
|
Applied Longitudinal Data Analysis
Statistical models and methods for the analysis of data arising
from longitudinal studies with repeated measurements on subjects over time.
Prerequisites: 6211, or Stat 6450, or Stat 6950
Learn more
|
Applied Survival Analysis
Introduction to time‐to‐event data analysis. Kaplan‐Meier estimation, log rank tests, proportional hazards regression analysis for censored or truncated data with extensions to time‐ dependent covariates and model building.
Prerequisites: PUBHBIO 6211 or STAT 6450 or STAT 6950 or permission of instructor. Not open to students with credit for STAT 6605
Learn more
|
Applied Statistical Analysis with Missing Data
Models and methods for the dataset with missing values, including imputation, likelihood‐based, and Bayesian models.
Prerequisites: 6211, or Stat 6201, or 6302, or 6802, or 6302, or 6450, or 6950 or permission of instructor.
Learn more
|
Biostatistical Collaboration
Basic biomedical research methodologies; collaborate with biomedical researchers to design experiments and plan analyses; protocol preparation; professional skills
development; statistical report preparation.
Prerequisites: Not open to students with credit for STAT 7755 (PUBHBIO 709). Cross‐listed in Stat 7755 (Biostat 709).
Learn more
|
PUBHBIO 7250
Credits: 1‐6
Special Topics
Regular class on special topics in biostatistics. Format will include lectures, readings, presentations and discussions in an area of special interest to students and faculty.
Prerequisites: Permission of instructor.
Learn more
|
Introduction to Causal Inference in Health Science Research
This is an introduction course to the commonly used statistical methods for causal inference. The course starts with potential outcome framework as the conceptual foundation for inferring
causality.
Prerequisites: B‐ or higher in PUBHBIO 6211, or permission of instructor
Learn more
|