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Fundamentals of Quantitative Reasoning in the Biomedical and Health Sciences

3rd term
Molecular Microbiology and Immunology
3 credits
Academic Year:
2021 - 2022
Instruction Method:
Asynchronous Online with Some Synchronous Online
Auditors Allowed:
Yes, with instructor consent
Grading Restriction:
Letter Grade or Pass/Fail
Course Instructors:
Margaret Wear

Introduction to Online Learning is required prior to participating in any of the School's Internet-based courses. none


Are you tired of poor argumentation in the news, in public debates or in even in scientific-professional contexts? Are you interested in learning a structured approach on how to be the most reasonable person in the room using practical logic? Do you enjoy analyzing and evaluating evidence to test hypotheses, and using them to engage in debates about the most pressing, global problems in science and society today? Then join us!

Provides a broad introduction to interdisciplinary, scientific reasoning using current problems from science and society. Explores the fundamentals of basic probability and statistics using real-world datasets from a variety of basic science disciplines. Introduces data analysis and visualization in the natural and biomedical sciences. Explains the importance of computational and quantitative methods for hypothesis testing in science, technology, and daily life.

Learning Objectives:

Upon successfully completing this course, students will be able to:

  1. State the relevance and use of models and hypotheses in research
  2. Explain the basics of hypothesis testing and data analysis in the life and biomedical sciences
  3. Employ suitable techniques for visualization or biomedical and health data
  4. Apply fundamental logic and ethics considerations to observational and experimental approaches to study current problems in science and society
  5. Practice rational argumentation and convincing yet truthful communication skills in interdisciplinary and public settings
Methods of Assessment:

This course is evaluated as follows:

  • 30% Problem sets
  • 20% Discussion Board
  • 30% Final Paper
  • 20% Peer-feedback

Instructor Consent:

No consent required

Special Comments:

This course is part of the JHSPH R3 Graduate Science Program.