Question 1

How many survey responses do I need?

Accepted Answer

For the standard 95 % confidence and ±5 % margin of error, 385 responses from a large population. Tightening to ±3 % needs 1,068; ±2 % needs 2,401. If the population is small the number drops: 370 for a population of 10,000, 278 for 1,000, 80 for 100. Enter your own targets above.

Question 2

What do confidence level and margin of error mean?

Accepted Answer

If 52 % of your sample say yes with a ±5 % margin at 95 % confidence, the true share in the population is between 47 % and 57 %, and a survey repeated many times would capture the true value in 95 % of runs. Confidence level sets how sure you want to be; margin of error sets how precise.

Question 3

Why is the expected proportion set to 50 %?

Accepted Answer

The term p(1 − p) is largest at p = 0.5, so 50 % gives the biggest, safest sample size. If you know the answer is lopsided — say 10 % of customers churn — set 10 % and the required sample falls by almost two thirds. Use 50 % when you have no prior information.

Question 4

Does population size matter?

Accepted Answer

Only when the sample is a noticeable fraction of it. For a country, a city or a customer base of a million, the population is effectively infinite and 385 is enough for ±5 %. For a company of 200 employees the finite population correction brings the sample to 132. That is why national polls of 1,000 people work.

Question 5

What about response rate?

Accepted Answer

The calculator gives the number of completed responses. If you expect 20 % of invitees to answer, invite five times as many: 385 responses needs about 1,925 invitations. Low response rates can also bias results if non-responders differ from responders.

Margin of error	Large population	Population 100,000	Population 10,000
±1 %	9,604	8,763	4,899
±2 %	2,401	2,345	1,936
±3 %	1,068	1,056	965
±5 %	385	383	370
±10 %	97	96	96

Sample Size Calculator

Sample size at 95 % confidence (p = 50 %)

The formula

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