Will your survey results ever perfectly match the population you’re studying? Probably not.

But you can get a good idea of how close you are by using a margin of error calculator. This handy tool will help you to determine whether the number of people you’re surveying is enough for you to feel confident about the accuracy of the data you collect.

Margin of error tells you how much you can expect your survey results to reflect the views from the overall population. Remember that surveying is a balancing act where you use a smaller group (your survey respondents) to represent a much larger one (the target market or total population.)

You can think of margin of error as a way of measuring how effective your survey is. The smaller the margin of error, the more confidence you may have in your results. The bigger the margin of error, the further they can stray from the views of the total population.

As the name implies, the margin of error is a range of values above and below the actual results from a survey. For example, a 60% “yes” response with a margin of error of 5% means that between 55% and 65% of the general population think that the answer is “yes”.

n = sample size • σ = population standard deviation • z = z-score

Let’s see the margin of error formula at work with an example.

Imagine you are trying to decide between Name A and Name B for a new product and your target market consists of 400,000 potential customers. This is your total population.

You decide to survey 600 of those potential customers. This is your sample size.

When you get the results, 60% of respondents say they prefer Name A. You need to input a confidence level in the margin of error calculator.

This number expresses how certain you are that the sample accurately reflects the attitudes of the total population. Researchers commonly set it at 90%, 95% or 99%.

Try inputting the numbers from this example in the margin of error calculator above. The calculator gives you a margin of error of 4%.

Remember that 60% of your respondents chose Name A? This margin of error means that, with 95% confidence, 56% to 64% of the total population (your target market) prefer Name A for your product.

We arrive at 56 and 64 by adding and subtracting the margin of error from your sample’s response.

People often mix up confidence intervals and confidence levels. The confidence level tells us how likely it is that a value is within the range of a confidence interval. To work out this range, we use the margin of error.

The margin of error helps us determine how much we might be off in our estimate. For example, a 95% confidence level means a 95% chance that the value is contained within the confidence interval. The higher the confidence level, the bigger the range (or interval), and that means allowing for a larger margin of error.

As we said, knowing your margin of error helps you understand whether the sample size of your survey is appropriate.

If your margin of error looks too big, you will want to increase the size of the sample so that the attitudes of the population surveyed match those of the total population more closely.

This means you will need to send your survey to more people.

The sample size calculator can help you easily determine how many people you need to take your survey.

Now that you know how margin of error is calculated and how it affects your results, let’s review the steps you need to follow to use these concepts in your survey design.

You can also find a more detailed explanation in this article about how to estimate your population.