About aiboxplot

What We Do

aiboxplot is a free suite of online statistics tools. We help students, teachers, researchers, and data analysts create and understand statistical charts — box plots, violin plots, histograms, scatter plots, pie charts, stem-and-leaf plots, Q-Q plots, and outlier analyses — without installing software, creating an account, or paying anything.

Every tool runs entirely in your browser. Paste your numbers, and the chart, the five-number summary, and the statistics are computed locally on your device. You can export publication-ready PNG, SVG, CSV, or XLSX files with one click — no watermarks, no sign-up.

Why We Built It

Descriptive statistics should be fast and approachable. Too often, making a simple box plot means firing up a spreadsheet, writing code, or signing up for a service that uploads your data to a server. We wanted a tool that is:

  • Instant — paste data, see the chart, no setup.
  • Private — computation happens in your browser; your dataset stays on your device (see our Privacy Policy).
  • Educational — every tool page explains the statistics behind the chart, with worked examples, formulas, and references to the original literature.
  • Free — the site is supported by unobtrusive advertising, not paywalls.

What Makes Us Different

  • Multi-dataset comparison — overlay up to 10 datasets in one box plot with independent colors, labels, and statistics.
  • Optional AI analysis — an on-page assistant can interpret your chart (skewness, outliers, group differences) and generate sample datasets. It is clearly disclosed in our Privacy Policy and only runs when you explicitly use it.
  • Real methodology — quartiles use linear interpolation (Hyndman & Fan type 7, the NumPy/pandas default); outliers use Tukey fences; histograms use the Freedman–Diaconis binning rule. Method notes and citations appear on every tool page.
  • A growing learning library — our Learn section publishes in-depth guides on reading, choosing, and computing statistical charts.

Who Is Behind aiboxplot

aiboxplot is built and maintained by an independent developer with a background in data analysis and front-end engineering, and a soft spot for Tukey-style exploratory data analysis. The project started as a teaching aid and grew into a full tool suite.

Get in Touch

Found a bug, have a feature request, or want to suggest a dataset or tutorial topic? Visit our Contact page — we read every message.