Statistical Representativeness Comparison¶
Learning Objective¶
Compare a synthetic dataset to a reference real dataset across verb frequency and session duration, identifying where the synthetic falls outside the acceptable tolerance.
- Bloom Level: Evaluate
- Bloom Verb: Compare
- Library: p5.js
Specification¶
The full specification below is extracted from Chapter 11: Synthetic Data Generation and AI-Assisted LRS Testing.
Type: interactive-infographic
**sim-id:** statistical-representativeness-comparison<br/>
**Library:** p5.js<br/>
**Status:** Specified
**Learning objective (Bloom — Evaluating):** Compare a synthetic dataset to a reference real dataset across verb frequency and session duration, identifying where the synthetic falls outside the acceptable tolerance.
**Layout:** Two side-by-side bar-chart pairs (top: verb frequency; bottom: session duration histogram); a tolerance-bar overlay; a side panel reporting pass/fail.
**Visual elements:**
- Top: side-by-side bar charts, each verb a pair (real left, synthetic right), with a tolerance band shown as a shaded background
- Bottom: side-by-side histogram bins (5-minute buckets, 0–60 min), real left, synthetic right
- Side panel: pass/fail badge per dimension, with the worst-deviating verb or bucket highlighted
**Interaction:**
- Slider: tolerance percentage (5% – 30%)
- Slider: synthetic-archetype mix (five sliders) — adjusting the mix re-generates the synthetic data and re-renders the comparison
- Preset buttons: "Match real cohort", "Over-engaged synthetic", "Under-engaged synthetic", "Skewed-archetype synthetic"
**Default canvas:** 1000×650px, responsive.
Implementation: p5.js for the bar charts, histogram rendering, and live re-computation when sliders change.