Calculate a survey sample size (number of respondents needed)

Calculate the number of respondents needed to acquire a correct sample size for a specific population. How to calculate the optimal sample size?

Sample size
Population size: How many people are in the group your sample represents? (The sample size does not change much for populations larger than 20,000.)
Margin of error:

 %

This is the plus-or-minus figure usually reported in newspaper or television opinion poll results. For example, if you use a margin of error of 4% and 47% percent of your sample picks an answer, you can be “sure” that if you had asked the question to the entire population, between 43% (47-4) and 51% (47+4) would have picked that answer.
Confidence level:

 %

This tells you how sure you can be of the error of margin. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the margin of error.
Required sample size: 0 Number of respondents needed
Estimated response rate:

 %

What percent of those asked to participate in the survey will do so. Response rates vary greatly depending on many factors including the distribution method (e-mail, paper, phone…), type of communication (B2C, B2B…), quality of the invitation, use of incentives, etc.
Number to invite: 0 This is the number of individuals out of the population you need to ask to partcipate, in order to achieve the required sample size based on the expected response rate.

Calculate the margin of error for the acquired number of respondents

After your survey is complete and you know the number of respondents you actually have, you can use this calculator to determine the actual margin of error.

Margin of error
Population size: How many people are in the group your sample represents? (The sample size does not change much for populations larger than 20,000.)
Number of respondents: The actual number of respondents that answered your survey.
Confidence level:

 %

This tells you how sure you can be of the error of margin. It is expressed as a percentage and represents how often the true percentage of the population who would pick an answer lies within the margin of error.
Margin of error: 0.00%  


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