Sample Size Calculator

How many people do you need to take your survey? Even if you’re a statistician, determining sample size can be tough. To make it easy, try our sample size calculator. We give you everything you need to to calculate how many responses you need to be confident in your results.

Calculate Your Sample Size:

Sample Size

*This sample size calculator uses a normal distribution (50%) to calculate your optimum sample size.

 

What is a sample size?

The number of completed responses your survey receives is your sample size. It’s called a sample because it only represents part of the group of people (or population) whose opinions or behaviour you care about. As an example, one way of sampling is to use a so-called “Random Sample,” where respondents are chosen entirely by chance from the population at large.

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Understanding sample sizes

Here are a few key terms you’ll need to understand to calculate your sample size and give it context:

Population size: The total number of people in the group you are trying to reach with your survey is called your population size. If you were taking a random sample of people across the United Kingdom, then your population size would be about 65 million. Similarly, if you are surveying your company, the size of the population is the total number of employees.

Margin of error: A percentage that describes how closely the answer your sample gave is to the “true value” is in your population. The smaller the margin of error, the closer you are to having the exact answer at a given confidence level.

If you want to calculate your margin of error, check out our margin of error calculator.

Confidence level: A measure of how certain you are that your sample accurately reflects the population, within its margin of error. Common standards used by researchers are 90%, 95% and 99%.

As an example, imagine you need to decide between two different names for your new product. According to your estimates, there are 400,000 potential customers in your target market. If you decide that the industry standard of 3% margin of error at a 95% confidence level is appropriate, then you will need to obtain 1065 completed surveys.

Calculating your sample size

If you’d like to do this sample size calculation by hand, use the following formula:

Sample size calculator equation

Population Size = N  |   Margin of error = e  |   z-score = z

e is percentage, put into decimal form (for example, 3% = 0.03).

The z-score is the number of standard deviations a given proportion is away from the mean. To find the right z-score to use, refer to the table below:

sample size calculation - z-scores

Things to watch out for when calculating sample size

  • A smaller margin of error means that you must have a larger sample size given the same population.
  • The higher your confidence level, the larger your sample size will need to be.

Tips for using the sample size calculator

If you are making comparisons between groups within your sample, you will need to take that into account when calculating sample size. If, for example, you split your sample into two groups of equal size, your sample size for each group is cut in half and your margin of error will increase. This can make it difficult to make meaningful comparisons between groups in your survey.

Returning to the scenario from earlier, your have a population of 400,000 potential customers and you need 1065 respondents to achieve a 95% confidence level with a 3% margin of error. If you wanted to see how the opinions of women and men differ (assuming they each make up 50% of the sample), you would end up with a sample size of 533 for a population of 200,000. With those numbers, your margin of error would go up – or you would need to increase your sample size.

Do you need more responses?

If the sample size calculator says you need more respondents, we can help. Tell us about your population, and we’ll find the right people to take your surveys. With millions of qualified respondents, SurveyMonkey Audience makes it easy to obtain survey responses from almost anyone.