Distribution Explorer

Probability Theory
shiny
distributions
pdf
cdf
quantiles
Visualise and compare discrete and continuous probability distributions with live parameter sliders
Published

April 17, 2026

Purpose

Every applied statistician eventually needs to recall the shape of a beta distribution with shape parameters \((2, 5)\), or the hazard function of a Weibull, or the relationship between the gamma and the chi-squared. The Distribution Explorer provides that recall visually: pick a distribution, drag the sliders, and see the PDF, CDF, quantile function, and hazard function update together.

User inputs

  • Distribution family (all major discrete and continuous families)
  • Distribution-specific parameter sliders with sensible ranges
  • Overlay mode: up to three distributions of the same family (or different families) plotted together
  • Reference lines: vertical lines at user-specified quantiles

Outputs

  • PDF or PMF in the top panel
  • CDF in the middle panel
  • Quantile function or hazard function in the bottom panel (user-selectable)
  • Summary table: mean, variance, skewness, kurtosis, median, mode (closed-form where known, numeric otherwise)
  • The \(d\), \(p\), \(q\), \(r\) R calls currently shown, ready to copy

Didactic value

The app makes relationships between families tangible: watching a binomial with \(n\) large approach a normal, watching a gamma degenerate into an exponential when shape equals one, watching a t-distribution converge to the normal as degrees of freedom grow. It also serves as a fluency tool – readers learn by inspection which parameters control location, scale, and shape.

Embedded in

  • Every distribution tutorial under probability/
  • inference/t-test-assumptions.md
  • regression-modelling/glm-families.md

Source code

Local: apps/03-distribution-explorer/

Run with:

shiny::runApp("apps/03-distribution-explorer")