Survey sample size calculator can help you determine how many people you need to survey to be statistically significant!

When considering conducting a survey, wondering how many responses are needed for a statistically significant dataset is one of the first questions. Determining the right survey sample size depends on many factors. But with our sample size calculator, you can answer this question online and for free. Using it is easy, though understanding the basic principles of how to get data that actually matters is the first step.

The number of people your sample will represent.

The industry standard is 95%.

Typically between 4% and 8%.

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You can’t get a survey response from everyone who belongs to a group of any size. What can be done is getting relevant responses from a portion of the group that provides comprehensive data from which to draw conclusions that will help you achieve your goals.

This is where sample size comes into play. With this calculation, you know how many responses you’ve gathered from a certain subgroup and if those are enough to be statistically significant. In other words, you want a representative sample that’s large enough to produce statistically significant results. You need to know:

- The math behind the survey sample size formula.
- How the sample size influences results.
- How to achieve statistical significance.
- What margin of error is.
- Different types of confidence levels.

Before diving deeper into the math behind the survey sample size formula, let’s explain some basic terms that will make the topic more understandable.

- S = Desired sample size needed to achieve statistical significance.
- N = Population size is the total number of people in the group you're surveying.
- Z = Score is how many standard deviations a data point is when compared to the population mean.
- Standard Deviation (σ) = Used in statistics to determine how dispersed data is compared to the average.
- Mean (μ) = Shows the average score for the characteristic being measured in a certain group, like the average IQ in the United States being 98.

When calculating sample size, it’s important to know a few facts. The first is knowing how large the population being researched is. If you’re conducting patient surveys for your healthcare institution, it’s important to know how many patients you have. You don’t need every single patient to fill out the survey. But if you have 500 patients, it’s unlikely that responses from only 10 patients will produce a statistically significant result.

Don’t let the statistical terminology confuse you. Master what each term means, then calculate the desired sample size and get valuable results from your survey. The margin of error is a percentage—from 0–100 percent—which tells you how much the results from your sample will vary compared to the entire population.

You want the margin of error to be as small as possible. This is achieved by having a large enough sample, since the margin of error is inversely proportional to sample size. The bigger the sample size, the smaller the margin of error.

The survey sample size confidence interval provides the level of uncertainty in your results. Every statistic (for example, 56 percent of the US population watches TV after work) is not 100 percent certain. The confidence interval tells you how uncertain a particular statistic is.

Along with the confidence interval, there is also the confidence level, which can be 99 percent, 95 percent, 90 percent, etc. Confidence level (for example, 95 percent) tells you that, if the survey is repeated, the results will be in a certain range 95 percent of the time.

If you want a survey with a high confidence level—in the 99 to 95 percent range—a large sample is needed. Luckily, our sample size calculator tells you exactly how many people will need to complete your survey based on the parameters you choose.

It’s important to note that having statistically significant responses is not always important. If you have a retail company and you’re conducting customer surveys, then every response matters. For example, you won’t ignore a certain problem that some customers have with a product, even if only a few bring it up in a survey. In practice, every response holds immense value.

On the other hand, when it comes to public sector surveys, having a large sample and statistically significant data is important. If the survey is about transportation priorities in Washington, DC, then it’s of utmost importance to gather responses from as many citizens as possible in order to best develop priorities. This will ensure that the majority is satisfied with the decisions that impact their everyday life.

After you collect valuable data, you may find our articles on how to analyze the survey data and tips for gaining better insights useful.

Now that you know the basic terminology and math behind the sample size calculator, it’s time for an actual sample size formula.

For example, if you’re surveying a population that has 1000 people—and you want your confidence level to be 95 percent (with a 5 percent margin of error)—then the minimum sample size for statistical significance would be 278 responses.

Figuring the sample size for your survey is hassle-free with our statistically significant sample size calculator. It will tell you precisely how many responses you need without having to make calculations manually. Try it out before focusing on which survey is right for your needs.

With our tools, you’ll get the most out of the data collected. As a bonus, you can get started right away by combining our survey templates with our sample size calculator. These tools will help you get valuable insights from the stakeholders whose opinions matter most.

It couldn't be easier to sign up for an account and begin exploring our survey templates, including many pre-written questions. SurveyPlanet has three plans to satisfy the needs of every user, all of which include powerful features and a wide range of survey templates, from education and employee surveys to market research and human resources surveys.

Choose the survey type that best suits your needs, calculate the sample size needed, and then get comprehensive data that you can rely on.

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