How many people do you need to take your survey? Even if you’re a statistician, determining survey sample size can be tricky.
Want to know how to calculate it? Our sample size calculator makes it easy. Here’s everything you need to know about getting the right number of responses for your survey.
Sample size is the number of completed responses your survey receives. It’s called a sample because it only represents part of the group of people (or target population) whose opinions or behaviour you care about. For example, one way of sampling is to use a “random sample”, where respondents are chosen entirely at random from the population at large.
With this definition in mind, let’s dive into the following topics:
Here are three 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 study. If you were taking a random sample of people across the U.K., then your population size would be just under 68 million. Similarly, if you were surveying your company, the size of the population would be the total number of employees.
Margin of error: A percentage that tells you how much you can expect your survey results to reflect the views of the overall population. The smaller the margin of error, the closer you are to having the exact answer at a given confidence level.
Sampling confidence level: A percentage that reveals how confident you can be that the population would select an answer within a certain range. For example, a 95% confidence level means that you can be 95% certain that the results lie between x and y numbers.
Wondering how to calculate sample size? If you’d like to do the calculation by hand, use the following formula:
N = population size • e = Margin of error (percentage in decimal form) • z = z-score
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:
|Desired confidence level||z-score|
Generally, the rule of thumb is that the larger the sample size, the more statistically significant it is. This means there’s less of a chance that your results happened by coincidence.
However, you might be wondering whether or not a statistically significant sample size matters. The truth is that it’s a case-by-case situation. Survey sampling can still give you valuable answers without having a sample size that represents the general population. Customer feedback is one of the surveys that does this, regardless of whether or not you have a statistically significant sample size. Listening to customers' thoughts will give you valuable perspectives on how you can improve your business.
On the other hand, political pollsters have to be extremely careful about surveying the right sample size, as they need to make sure it’s balanced to reflect the overall population. Here are some specific use cases to help you work out whether a statistically significant sample size makes a difference.
|Value increased||Value decreased|
|Population size||Accuracy decreases||Accuracy increases|
|Sample size||Accuracy increases||Accuracy decreases|
|Confidence level||Accuracy increases||Accuracy decreases|
|Margin of error||Accuracy decreases||Accuracy increases|
Working on an employee satisfaction survey? All HR surveys provide important feedback on how employees feel about the work environment or your company. Having a statistically significant sample size can give you a more holistic picture of employees in general. However, even if your sample size isn’t statistically significant, it’s important to send the survey anyway. HR-related surveys can give you important feedback on how you should improve the workplace.
As we pointed out earlier, customer satisfaction surveys don’t necessarily have to rely on having a statistically significant sample size. Although it’s important that your responses are accurate and represent how customers feel, you really should be taking a closer look at each answer in a customer satisfaction survey. Any feedback, be it positive or negative, is important.
When conducting a market research survey, having a statistically significant sample size can make a big difference. Market research surveys help you discover more information about your customers and your target market. Therefore, a statistically significant sample size can easily help you discover insights into your overall target market. It also ensures that you’re getting the most accurate information.
For education surveys, we recommend obtaining a statistically significant sample size that represents the population. If you’re planning to make changes in your school based on feedback from students about the institution, administrative staff, teachers, etc., then a statistically significant sample size will help you get results to lead your school to success. If you’re planning to just receive feedback from students for the sake of seeing what they think – and not necessarily making a change in the system – then a statistically significant sample size might not be as important.
When conducting healthcare surveys, a statistically significant sample size can help you find out which health issues are a greater concern for your patients than others. It can also help you reach conclusions in terms of medical research. However, if you’re using healthcare surveys for patient satisfaction reasons or questioning patients about their regular care, a statistically significant sample size might not be as important. Without it, you’re still able to obtain valuable information from individual patients about their needs and experience.
On a day-to-day basis, you might want to send surveys to friends, colleagues and family, etc. In this case, it really depends on what you're looking for from your survey. If you’d like your results to be used as evidence, then a statistically significant sample size is important. If not, and you’re just using SurveyMonkey for fun, sending your survey to just a few people won’t hurt.
Don’t just take a guess at how many people should take your survey, and don’t get bogged down with probability sampling or probability distribution models. Instead, use our sample size calculator. Familiarise yourself with sample bias, sample size, statistically significant sample sizes and how to obtain more responses. You'll soon have everything you need to obtain better data for your survey.
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 people around the world instantly, from almost anyone.
SurveyMonkey Audience has millions of respondents who are ready to take your survey.