Presenter: Alexander Y. Mitrophanov, PhD, Senior Statistician, ABCS/FNLCR (Frederick, MD)

The P-value is a cornerstone notion in statistics that is often used as the main deciding factor in determining the conclusiveness and reliability of empirical findings. Despite its ubiquity as a data-analysis feature in biological sciences, the rigorous definition, study, and interpretation of P-values can be elusive for practitioners. In this lecture, I will de-mystify P-values and explain their proper use in statistical hypothesis testing and related methodologies. Our main goal will be to look beyond the simplistic “P ≤ 0.05” rule and learn to regard P-values as valuable analytic tools rather than a mere formality. Beginner level of statistical knowledge is expected, intermediate is preferred.

This will be a hybrid event. Please register at this link.

This session will be recorded, and materials will be shared with attendees a few days after the event.

For additional details and questions, please contact Natasha Pacheco (natasha.pacheco@nih.gov), Advanced Biomedical Computational Science group, Frederick National Laboratory for Cancer Research.