Course Description

The goal of this course is to teach students how to gain and communicate insights from biomedical data. We will learn concepts such as data wrangling, exploratory data analysis, statistical inference, and linear and mixed modelling techniques. Students will learn to use the statistical programming language R (free and open source) throughout the complete research pipeline: importing, wrangling, visualizing, analyzing, interpreting, communicating, and collaborating. We will also learn to create and maintain efficient workflows for reproducible research. We will use modern teaching materials including to introduce and reinforce R skills in an interactive self-guided environment, and the free online textbooks “Modern Dive” (Ismay & Kim, 2018) and “Data Analysis for Life Sciences” (Izarry & Love, 2015).

The course is organized into 5 blocks: working with data (3 weeks), linear models (3 weeks), inference (3 weeks), mixed models (1.5 weeks), and communication (1.5. weeks). Each class will be a mixture of didactic lectures (≈20 minutes), followed by hands-on labs to apply knowledge to real-world data. Pre-work will involve relevant readings and sometimes coding assignments to prepare for labs. For students who already have facility with R, more advanced stretch exercises will be provided. Each block will wrap up with an in-depth lab to allow students to integrate and iterate on knowledge gained, and review and relate back to previously learnt concepts. Final projects will be described in the first week of class.

Learning Outcomes

  • Develop and clearly describe a statistical analysis plan, from start to finish.
  • Work independently with data, including wrangling, tidying, visualizing, and basic analyses.
  • Accurately interpret results from basic inferential statistical analyses.
  • Understand assumptions and limitations to statistical procedures.
  • Know about the types/scope of questions one can ask about data.
  • Identify statistical questions/problems that require advanced methods out of skill set.
  • Proficient use of tools and vocabulary to facilitate effective collaboration with advisors, biostatisticians, and other team members.


Select lab sessions will require a finished submitted in-class and/or accompanying homework assignment (due via electronic submission prior to the next meeting time). Each participant must also present during the final two weeks of class. A portion of the grade will reflect attendance. Final grading rubric will be made available at the start of class.

We will be assigning some DataCamp courses/chapters to help you learn R alongside data science and analysis skills. I will enroll you in our course group on the DataCamp site using your OHSU email address, unless you provided a different email account in our pre-course survey. You will then receive an email from DataCamp with a link to register on their site. You may register with your OHSU username, but you do not have to- you may pick a different username. Please note:

  • You should not use the same password for DataCamp as you use for OHSU; you should choose a different password.
  • You are not obligated to purchase any services from DataCamp, although you are welcome to if you choose to do so.
  • You are also not required to fill in any additional profile information for DataCamp.


Laptops will be used during the hands-on, in-class labs. If you do not have access to a laptop, please consult with the course director to make arrangements to borrow a laptop with the necessary software installed.


Attendance and class participation are expected of all students. Requests for time off must be submitted to the course director in a timely manner.

Student Resources

Statement Regarding Students with Disabilities

OHSU is committed to inclusive and accessible learning environments in compliance with federal and state law. If you have a disability or think you may have a disability (mental health, attention-related, learning, vision, hearing, physical or health impacts) contact the Office for Student Access at (503) 494-0082 or to have a confidential conversation about academic accommodations. Information is also available at Because accommodations may take time to implement and cannot be applied retroactively, it is important to have this discussion as soon as possible.

Student Evaluation of Teaching

Course evaluation results are extremely important and used to help improve courses and the learning experience of future students. Responses will always remain anonymous and will only be available to instructors after grades have been posted. The results of scaled questions and comments go to both the instructor and their unit head/supervisor. Refer to Student Evaluation of Teaching, Policy No. 02-50-035.

Syllabi Changes and Retention

Syllabi are not to be considered a contract. Information contained in syllabi, other than the course grade and absence policies, may be subject to change as deemed appropriate by the instructor.

Professional Conduct Expectations

OHSU faculty, staff, and students are expected to conduct themselves in accord with the high ethical standards expected of health professionals as noted in the OHSU Code of Conduct. In addition to the OHSU Code of Conduct, refer to your program’s handbook for additional details.

Commitment to Diversity & Inclusion

OHSU is committed to creating and fostering a learning and working environment based on open communication and mutual respect. If you encounter sexual harassment, sexual misconduct, sexual assault, or discrimination based on race, color, religion, age, national origin, veteran’s status, ancestry, sex, marital status, pregnancy or parenting status, sexual orientation, gender identity, disability or any other protected status please contact the Affirmative Action and Equal Opportunity Department at 503-494-5148 or Inquiries about Title IX compliance or sex/gender discrimination and harassment may be directed to the OHSU Title IX Coordinator at 503-494-0258 or

Modified Operations, Policy 01-40-010

Students should review the Student Portal, O2, or call OHSU’s weather alert line at 503-494-9021 for the most up-to-date information on OHSU-wide modified operations which include but are not limited to delays or closures for inclement weather.

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