Purpose and scope

DistriScope is an English-language educational statistics workspace for students, researchers, and analysts. It connects equations, visualizations, and calculations so users can inspect how assumptions and parameters affect a result. It is not a clinical, financial, regulatory, or automated decision system. Outputs are starting points for learning and exploratory analysis; consequential work should be reproduced with validated software and reviewed by a qualified statistician.

Calculation approach

The application performs supported calculations in the browser using the established jStat numerical library together with reviewed local formulas. Chart.js supports interactive plots, while KaTeX renders mathematical notation. Each tool defines its own input validation and supported parameter ranges. The Distribution Explorer evaluates probability functions and cumulative behavior; the Comparator and Relationship Explorer visualize controlled family comparisons; Data Fitting estimates supported candidate models and reports available diagnostics; the Calculator evaluates selected probability and hypothesis-testing procedures.

Library use improves consistency but does not remove the need to inspect parameterization, floating-point precision, edge cases, and statistical assumptions. Different textbooks and software packages may define scale, rate, degrees of freedom, or tail conventions differently. DistriScope explanations aim to name the convention in context. When reproducing a result elsewhere, compare definitions before comparing numbers.

Editorial and review principles

Definitions answer the statistical question directly before adding detail.
Worked examples distinguish the numerical output from its practical interpretation.
Assumptions and limitations appear near the relevant tool instead of being hidden in a disclaimer.
We avoid treating p-values as the probability a hypothesis is true or visual similarity as proof of model fit.
Pages include a review date so material changes can be tracked.

Current public guidance was reviewed on 2026-07-30. The source code is available through the project’s GitHub repository, which provides a direct way to inspect implementation details and report reproducible issues.

Accuracy, uncertainty, and responsible use

Numerical software can produce a precise-looking answer from an inappropriate model. Before interpreting output, confirm the sampling design, outcome scale, independence structure, missing-data handling, and distributional conditions. Inspect effect sizes and intervals where available, not only threshold-based significance. Tail probabilities and extreme parameter values may be more sensitive to numerical precision than central probabilities.

If a result informs health, safety, employment, credit, public policy, or another high-impact decision, do not rely on DistriScope alone. Retain the original data, document every transformation, reproduce the calculation independently, and obtain appropriate professional review.

Corrections and contact

DistriScope is maintained as an open project. To report a calculation, accessibility, or content issue, open a reproducible issue in the GitHub issue tracker. Include the tool, inputs, expected result, comparison source, browser, and steps needed to reproduce the problem. Corrections should update both the implementation and the related explanation when they affect interpretation.