Understanding Polling — Margin of Error MicroSim¶
Learning Objective¶
Students will interpret (Bloom L2 — Understand) polling data including margin of error and apply (Bloom L3 — Apply) this understanding to distinguish between statistically significant differences and statistical ties.
- Bloom Level: Apply (L3)
- Bloom Verb: Interpret, Apply
- Library: p5.js
Specification¶
The full specification below is extracted from Chapter 9: "Chapter 9: Political Opinion, Media, and Civic Reasoning".
Type: MicroSim
**sim-id:** polling-margin-of-error<br/>
**Library:** p5.js<br/>
**Status:** Specified
**Learning objective:** Students will *interpret* (Bloom L2 — Understand) polling data including margin of error and *apply* (Bloom L3 — Apply) this understanding to distinguish between statistically significant differences and statistical ties.
**Design:**
- A horizontal bar chart showing two candidates ("Candidate A" and "Candidate B") with adjustable bars
- Sliders on the left:
- "Sample size": 100 to 5,000 (default 1,000)
- "Candidate A support": 40% to 60%
- As sliders adjust, the chart shows:
- Each bar with its percentage
- Error bars (±margin of error) around each bar
- A color-coded verdict: "STATISTICAL TIE" (if ranges overlap) or "CLEAR LEAD" (if ranges don't overlap)
- The formula displayed: Margin of Error = 1 / √(sample size) × 100%
- A note at the bottom: "Real margins of error are more complex, but this approximation captures the key relationship: larger samples → smaller margin of error → more precise estimates."
- Educational callout: "If a poll says A leads 52%-48% with ±4% margin, can you call a winner?" → No: A's range is 48%–56%; B's range is 44%–52%. Overlapping ranges = statistical tie.
- Canvas: 100% width × 450px; responsive