This article explains what p-values measure, why they become unreliable at scale, and how to correct for multiple testing. Interactive visualizations are essential to the scientific argument because they allow readers to directly manipulate the relationship between sample size, effect size, and p-values; revealing how the same threshold can be crossed by trivial effects given enough data. The resample-able multiple testing grid demonstrates the inevitability of false positives under repeated testing, while the dynamic correction method comparison shows how Bonferroni and Benjamini-Hochberg procedures make different trade-offs between sensitivity and specificity. Static figures cannot convey these parameter-dependent relationships or let readers explore the bias-variance tradeoff in real time, which is central to understanding when "statistical significance" diverges from scientific significance.
Science publishing is broken in a specific way: the dominant format is a static PDF designed for print, yet the research it describes increasingly relies on simulations, interactive figures, and reproducible computation that a PDF cannot express. Vivum is an open index for interactive scientific articles, and this work requires the web medium to make its argument. Authors self-publish at any public URL and retain full ownership; Vivum provides discovery, community peer discussion, and a formal review pathway. When an article crosses a community threshold of votes, it enters structured peer review covering significance, reproducibility, and clarity, resulting in a citable DOI via Zenodo. Vivum itself is the demonstration of its own thesis: this platform is a live, interactive system, not a document, and every design decision is inspectable and open.
The scientific paper has not changed in form since 1665. It started as text with static figures and in 2026 it continues being that way. This article argues that the web-native format is not merely a more convenient delivery mechanism for the same content, but a medium capable of making arguments that a PDF cannot, while also serving as one of the founding submissions to Vivum, demonstrating the format it advocates.
The Kolmogorov-Smirnov test compresses the difference between two distributions into a single number: the maximum vertical gap between their empirical CDFs. This article builds geometric intuition for the statistic through three interactive figures, covering what D measures and where it appears, how the p-value scales with sample size, and why the same value of D can signal strong model performance in one context and a worrying data drift in another.