Online Training Courses

Online Modules

Below are the current online modules offered by the CTSI and the Division of Biostatistics.

Introduction to Clinical Research: A Web-Based Self-Study Program



Introduction to Clinical Research

1) Designing a Research Question (Robert Link)


2) Subjects and Sampling (Robert Link)


3) Clinical Results-Assessing Outcomes (Robert Link)


4) Hypothesis Testing (Robert Link)



Survey of Clinical Study Methodologies

1) Cohort Studies (Arthur Fierman)

In Introduction to Clinical Research module, we provide an introduction to the design and performance of clinical research projects. Text, video and animation intersperse with multiple choice and free text questions to provide you with an easy-to-follow, on-your-own time way to understand the basic principles of clinical research. In Survey of Clinical Study Methodologies module, we examine individual study methodologies: their strengths, their weaknesses, and when and how to decide which methodology may be right for your individual study.

To access the modules click on the links above or, please:

  1. Log in to NYU Compass with your Kerberos ID or Net ID
  2. If you do not have a Kerberos ID or Net ID and Password, click on 'Non-NYU Login' and follow the instructions provided
  3. Click on 'CTSI TREC' tab, located on the right-hand side of the webpage
  4. Click on any of the modules to view content

For technical questions, please contact IT support.

The Division of Biostatistics’ Introduction to Biostatistics Online Modules




Introduction to Biostatistics

Introduction to Biostatistics, developed by Johns Hopkins Bloomberg School of Public Health and adapted by NYU School of Medicine’s Division of Biostatistics, presents fundamental concepts of statistical theory and practice as they are applied in the context of translational and clinical research. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions; statistical hypothesis testing; and random sample and other study design issues.

To access the module, a Kerberos ID is required. If you do not have one, please contact Daniel Cobos.

For technical questions, please contact IT support.