Sample Size Matters

Could you have misconceptions about data visualization and statistical analysis that may affect the outcomes of your research? Misconceptions and problems with data visualization and statistical analysis are common in published studies. In this program, learners identify and correct misconceptions about data visualization and statistical analysis that are common in the basic biomedical sciences and other disciplines using small sample size studies.

What misconceptions do you have? Take a quiz to find out.

Sample Size Matters is an online program for graduate students and research professionals. Participants learn to apply the knowledge and skills gained to improve rigor, transparency and reproducibility in their own research.

Program highlights

  • Anytime, anywhere learning
  • Self-directed and self-paced
  • Certificate of completion granted upon successful completion of the program

Registration

Due to system updates and changes, registration for this program will be paused until September 2022. Please check back!

Curriculum

  • Sample Size Matters includes approximately 10 hours of content.
  • Participants have up to six months to complete the program.
  • The content is accessible for one year after admission.
  • A score of 80% or higher is required on each knowledge check to move to the next module.
  • A certificate of completion is granted upon successful completion of the program.

Objectives

After completing the program, learners will be able to:

  • Recognize problems with current standard practices in basic biomedical science research
  • Identify solutions for problems with current standard practices in basic biomedical science research

Faculty

Sample Size Matters was created by Tracey L. Weissgerber, Ph.D., and Stacey J. Winham, Ph.D. Drs. Weissgerber and Winham have collaborated on a number of high-impact studies in the field since 2014, including their influential 2015 PLOS Biology paper on bar graphs.

Dr. Winham is a faculty member in the Division of Computational Biology, Department of Quantitative Health Sciences, and leader of biostatistics education at Mayo Clinic.

Dr. Weissgerber is a former Mayo Clinic faculty member in the Division of Nephrology and Hypertension and a group leader and metaresearcher at the Berlin Institute of Health Quality, Ethics, Open Science, Translation (QUEST) Center at Charité — Universitätsmedizin.

Contact

The CCaTS Education Contacts page contains a list of team members who can assist you with questions.