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Visual Guides/Sample Size, Margin of Error & Survey Design
STATISTICS

Sample Size, Margin of Error & Survey Design

Calculate exactly how many people you need to survey for a given precision. Explore cost-precision tradeoffs and discover how polling organizations design surveys with stratification and weighting.

MOE adjusted
Confidence level changed
Proportion adjusted
Survey cards: 0/3
Case study viewed

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Calculator Inputs

±3%

How close to the true value do you need?

1%10%

Confidence Level

95% CI: if you repeated the survey 100 times, ~95 would include the true value

p = 50%

Use 50% if unsure: this gives the largest (most conservative) sample size

10%50% (max)90%

FPC reduces required n when population is small relative to sample

Required Sample Size

1,068

Survey 1,068 people to estimate the proportion within ±3% with 95% confidence

Standard Error

1.530%

Actual MOE

±3%

p(1-p)

0.2500

Formula

n = z² × p(1−p) / MOE²

Practical Estimates

Total budget

$5,340

20%
0%50%

Adjusted contacts needed

1,335

with 20% non-response

Time estimate

11 days

at 100 surveys / day

Cost-Precision Curve

Drag the gold dot to explore how sample size affects margin of error

0%2%4%6%8%10%12%505001K1.5K2K2.5K3KSample Size (n)MOE (%)n=100: MOE≈10%n=400: MOE≈5%n=1600: MOE≈2.5%1068 → ±3%

Key insight: Notice the curve flattens: diminishing returns after ~n=400. Doubling sample size beyond that barely shrinks the MOE.

MOE Comparison Table

Based on 95% confidence, p = 50%. Highlighted row matches your current MOE setting.

MOERequired nCostTime
±1%9,604$48,02097 days
±2%2,401$12,00525 days
±3%current1,068$5,34011 days
±5%385$1,9254 days
±10%97$4851 day

Key insight: Halving MOE quadruples sample size: precision is expensive.

Survey Design Principles

0/3 explored
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