Most surveys are run for research purposes based on the compiled information for a study sample, not the total population. Because of this, the margin of error is an item to consider when running the sampling. The margin of error calculator measures the maximum amount by which the outcome of our sample might differ from the total population.
Given that most responses from a survey can be presented in terms of percentages, the result of the calculation is too shown as a percentage.
Our margin of error calculator has the objective of showing the researcher how much they can trust in the outcome that was obtained during the survey application phase of their research project.
If you want to know more about sampling, we recommend you visit our article: Types of sampling.
The margin of error is the considered amount of error that might be in a random sampling process for any research project, especially when running questionnaires or surveys.
It's important to be aware of this during any research project since it determines the desired confidence level regarding the outcome of the entire research.
The narrower the margin of error, the broader the degree of certainty on the research outcomes.
Two pieces of information are needed to calculate the margin of error for a sample. The margin of error is calculated from:
To calculate margin of error, you need to follow the following margin of error formula:
Where σ (the population standard deviation) is divided by the square root of the n (sample size), and the result is multiplied times z (tabulation based on the determined confidence level value) in the above-mentioned margin of error formula.
|Confidence Level (in percentage)
As a first step, set the size of the total population considered for your research project in the indicated box.
Then set a confidence level. The most common standard value to researchers is 95%. Remember: the narrower the confidence level, the broader the margin of error.
Finally, set the sample size. To do this, you should already know the sample size concerning the total population. If you don't know it yet, check out our Sample Size Calculator.
There! Automatically, you’ll be able to know the ideal margin of error (MoE) for the research project you’re working on.
Margin of error:
For example, say you have a new milkshakes business, and you're training new employees to fill the cups with the right amount of ice cream, 10oz each.
Therefore, you want to calculate the average weight of the cones produced during a workday, including the margin error. Instead of weighing each cup, you ask every employee to weigh and register a sample of the served cups randomly and take notes.
For 50 sampled cups, you found an average of 10.3oz. Say the standard deviation for that population is 0.6oz. So, how would you calculate the margin of error with a confidence level of 95%?
Based on the 50 cups sample, the average weight is 10.3oz with a margin error of approximately 0.17oz. In other words, the possible interval for the average weight of all the big seized cones produced for a workday is estimated (with a confidence level of 95%) between 10.30 - 0.17 = 10.13oz and 10.3 + 0.17 = 10.47oz.
It is essential to select an adequate survey sample size to get credible results from a survey and use them to inform critical business decisions. You will not get reliable results if you choose a sample that is too small. The margin of error is reduced as the sample size increases. Here are some essential factors to consider when determining sample size:
The first step in determining sample size is estimating the population being researched. Here, the population is the entire or the larger group you want to research, and the sample size is the number of people you need to question to achieve a representative sample.
There is no way to be 100 percent accurate with surveys. The margin for error is also referred to as the confidence interval. The confidence interval tells you how far your survey data can be from what the population means. A margin of error tells you how close to the actual population value you can expect a survey result to be.
The confidence level indicates how well the sample accurately reflects its entirety. The greater the size of the sample, the greater the confidence in the results. The smaller your sample size, the less confident you can be in your results.
Standard deviation measures the amount of variation among individual data points in a population. It measures how much a normal distribution can vary from one point to another.
A low population standard deviation suggests the values are grouped around the mean number. In contrast, a high population standard deviation means they are scattered across a range with some tiny and big outliers.
If you are about to run a research project and you want to collect the appropriate number of samples, we have a few suggestions for you:
Now that you’ve followed these steps, you know exactly how many people should receive your survey for you to obtain the desired outcome.
Calculating the margin of error will help you determine the possibility that the survey result will be close to the result if the entire population is surveyed. As a result, its worth influences how accurate your survey is. The following are some of the benefits of using a Margin of Error Calculator:
The margin of error calculator is a way of measuring how effective your survey is. The narrower the margin of error, the more confidence you can have in the results—the broader the margin of error, the further the opinions from the total population.
We hope this tool will be quite useful for your research (or other projects). Remember that with QuestionPro, you'll be able to use these values to obtain real value thanks to our Survey Software.
You can start right now by using QuestionPro for free or connect with one of our executives to clear your doubts about our platform.
Finally, we recommend the following read: Population vs. Sample.