ROPE & HDI Decision Dashboard

How posterior width, effect size, and ROPE boundaries drive Bayesian decisions

Adjust the posterior (via n and k/n) and the ROPE boundaries to see how the HDI–ROPE relationship changes the decision in real time.

▾ click for more detail

Posterior (Beta conjugate)

Sample size n 20

Observed proportion k/n 0.750

Prior: Beta(α₀, β₀) — each 1

ROPE centre θ₀ 0.55

ROPE half-width ε 0.100

Level 95%

—

Posterior mean

—

HDI bounds

—

P(in ROPE)

—

P(above ROPE)