14:30
17/04/2026 - 14:30 - ISBA C.115 + Online
(UCLouvain)
Will give a presentation on :
P‑values and effect sizes are among the most widely used—and sometimes misused—quantities in statistical analysis. The p‑value often appears as the sole metric in weak statistical reports, while effect sizes are increasingly promoted to complement or replace p‑values by quantifying the magnitude of an effect rather than its mere statistical significance. Although these concepts seem straightforward to scientists with a solid statistical background, their practical implementation can reveal surprising subtleties.
In this seminar, we explore two situations where the gap between the conceptual definitions of these quantities and their real‑world computation becomes especially important. First, we examine how common statistical software computes p‑values and how these implementations can quietly diverge from textbook definitions—sometimes with the intention of reducing misinterpretation, but at the cost of obscuring key conceptual ideas. Second, we investigate how the treatment of “absent” predictors in linear models influences effect‑size estimation in multimodel averaging, leading to potentially large differences depending on the chosen parameterization and interpretation.
Through these two examples, the seminar highlights why even basic statistical quantities deserve a closer look, and how understanding the nuances behind them can improve both statistical practice and critical interpretation.
Teams Link: https://teams.microsoft.com/meet/349902929081522?p=DQKvIriuXSAtcyWEcn