The Statistical Analysis of Research Data (SARD) is designed to provide an overview of the general principles of statistical analysis of research data. The SARD course will be held virtually by WebEx on January 21, 23, 27, and 29, 2026, from 1:00 to 5:00 PM. The first day will feature univariate data analysis including descriptive statistics, random sampling and estimating a population mean. The second day will describe inferential statistics, two sample tests of means and small versus large sample consideration. The third day will feature bivariate statistics including simple linear regression and regression diagnostics. The fourth day will discuss multivariate data analysis including regression, non-parametric tools and goodness of fit tests.
- The participation of NIH clinical and postdoctoral fellows are encouraged.
- Class size is limited to the first 100 registrants.
Instructor
Paul Thurman, DBA, Columbia University
Registration
Registration is now OPEN, please register at https://events.cancer.gov/cct/sard. Registration will close on January 20, 2026.
Location and General Information
The virtual sessions will be held from 1:00 to 5:00PM each day via WebEx. All lectures will be recorded and archived. Individuals with disabilities who need Sign Language interpreters and/or reasonable accommodation to participate in this event should contact Dr. Terry Moody (moodyt@nih.gov).
Related Training Opportunities
Translational Research in Clinical Oncology (TRACO) hosted by Dr. T. Moody is offered primarily for NIH postdoctoral fellows. This fall course is part of a developing curriculum for training of NCI clinical and postdoctoral fellows.
Demystifying Medicine has 2 hours of lecture each week from January-May and the course is hosted by Dr. Irvin M. Arias.
For additional opportunities for postdoctoral training at NIH, view https://www.training.nih.gov/.
More Information
Contact Dr. Terry Moody at moodyt@mail.nih.gov or 240-276-7785.
Organizing Committee
William. D. Figg, Pharm.D.
Terry Moody, Ph.D.
Chanelle Case Borden, Ph.D.
Faculty
Paul Thurman, MBA