Data

Confidence Intervals & Sample Size: How Much Data Do You Actually Need?

Every survey, every experiment, every customer research project hinges on one decision: how many people do I need? Get it wrong and you either waste budget or make decisions on noise.

Confidence Interval Formula

CI = x̄ ± z × (σ ÷ √n)

Where z is the critical value (1.96 for 95%), σ is standard deviation, and n is sample size. Use our Confidence Interval Calculator to skip the algebra.

Margin of Error in Plain English

If a poll says “47% support, ±3% margin of error at 95% confidence,” it means: if we ran this poll 100 times, 95 of them would land between 44% and 50%. Our Margin of Error Calculator handles this directly.

Sample Size Cheat Sheet (95% confidence, 50% prevalence)

• ±10% margin → ~96 respondents
• ±5% margin → ~385
• ±3% margin → ~1,067
• ±2% margin → ~2,401
• ±1% margin → ~9,604

Doubling precision quadruples cost. Plan for the precision you actually need.

The Diminishing Returns Trap

Going from n=100 to n=400 cuts your error in half. Going from n=400 to n=1,600 cuts it in half again — for 4× the budget. Most business decisions are fine at ±5%.

Calculate Required Sample Size

For a planned experiment, use our Sample Size Calculator. You’ll need: baseline rate, minimum detectable effect, significance level (0.05), power (0.80).

FAQs

What if my response rate is low? Sample size refers to completed responses. Plan invites accordingly.

Is 95% confidence always right? No — high-stakes medical or financial decisions often use 99%.