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Margin of Error Calculator FullScreen

Estimate the margin of error for a sample proportion or sample mean using our online calculator. By inputting the sample size, confidence level, and either the population proportion (for proportion estimation) or the population standard deviation (for mean estimation), you can calculate the margin of error.

Margin of Error (MOE) Calculator


what is Margin of Error Calculator

A margin of error calculator is a statistical tool used to calculate the maximum likely difference between a sample estimate and the true population parameter. It is primarily used in surveys or polls to determine the precision or reliability of the results.

Here's how a margin of error calculator works:

  1. Determine the Confidence Level: The first step is to select the desired confidence level, which represents the level of certainty you want to have in your estimates. Commonly used confidence levels are 95% or 99%.

  2. Collect Sample Data: Gather data by taking a random sample from the population of interest. The sample size should be determined based on factors such as the desired level of precision and the variability in the population.

  3. Calculate Sample Proportion or Mean: Depending on the type of data being collected, calculate the sample proportion (for categorical data) or the sample mean (for numerical data).

  4. Determine Standard Error: The standard error is a measure of the uncertainty associated with the sample estimate and reflects the variability inherent in the sampling process. It is calculated using the formula specific to the type of data and the sampling method employed.

  5. Calculate Margin of Error: Using the standard error and the selected confidence level, the margin of error is calculated by multiplying the standard error by the appropriate critical value from the standard normal distribution (Z-score). The critical value is determined based on the desired confidence level.

  6. Interpret Results: The margin of error provides an interval around the sample estimate within which the true population parameter is likely to be found. It is typically expressed as a range around the estimate, such as ± X%, where X is the calculated margin of error. The larger the margin of error, the less precise the estimate.

Margin of error calculators can be found online or as part of statistical software packages. They simplify the process of calculating the margin of error and provide a measure of the likely range of error in survey or poll results.

If you provide me with the specific sample size, confidence level, and sample estimate, I can assist you further by calculating the margin of error for your data.

The Margin of Error in Statistics

The majority of surveys that are conducted for research purposes are based on information that is collected from a sample population as opposed to the full population (a census). As the sample is only representative of the full population, it is likely that some error will occur, not in terms of the calculation, but in terms of the sampling. That is, a sampling error will emerge because the researchers did not include everyone that exists within a given population. The MOE measures the maximum amount by which the sample results may differ from the full population. As most responses to survey questions can be presented in terms of percentages, it makes sense that the MOE is also presented as a percentage.

Margin of Error Formula

The Margin of Error (MOE) Calculator uses the following formulas:

1. MOE = z * √p * (1 - p) / √n

2. MOE (with finite population correction) = z * √p * (1 - p) / √(N - 1) * n / (N - n)


MOE  is the margin of error,

z  is the z-score associated with a level of confidence,

p  is the sample proportion, expressed as a decimal,

n  is the sample size,

N is the population size.

To estimate the sample size, take a look at our sample size calculator.

Margin of Error Calculation Example:  A market research agency conducted a survey to identify how many mobile phone users use their devices to access social media. They surveyed 1000 mobile phone users and found that 540 regularly used their devices to access their social media profiles.

Let's assume that we require a 95% level of confidence; as such, the z-score = 1.96.

The sample population, p, is 540 / 1000 = 0.54. (The sample size, n, was 1000.)

As such, the margin of error in this survey is as follows:

MOE = z * √p * (1 - p) / √n

MOE = 1.96 * √0.54 * (1 - 0.54) / √1000

MOE = 0.977 / 31.623 * 100 = 3.089%

These results indicate that the market research company can conclude with 95% confidence that 54% of mobile phone users use their device to access social media, give or take 3%.

Margin of Error Calculator example

Certainly! To calculate the margin of error for a sample proportion, you can use the formula:

Margin of Error = Critical Value * Standard Error

Here's an example to demonstrate how to calculate the margin of error:

Let's say we conducted a survey on a random sample of 800 people to estimate the proportion of individuals who support a particular candidate in an upcoming election. From our sample, we found that 450 individuals support the candidate.

Step 1: Determine the confidence level.

The confidence level determines the level of certainty you want to have in your estimate. Let's assume we want a 95% confidence level, which is commonly used in many studies.

Step 2: Find the critical value.

The critical value is determined based on the desired confidence level and the sample size. For a 95% confidence level, the critical value can be obtained from a standard normal distribution table or using statistical software. The critical value z* for a 95% confidence level is approximately 1.96.

Step 3: Calculate the standard error.

The standard error measures the variability in the sample proportion estimate. It can be calculated using the formula:

Standard Error = sqrt((p * (1 - p)) / n)


  • p is the sample proportion (450/800 in our example)
  • n is the sample size (800 in our example)

Let's calculate it:

p = 450/800 ≈ 0.5625 Standard Error = sqrt((0.5625 * (1 - 0.5625)) / 800) ≈ 0.0174

Step 4: Calculate the margin of error.

Using the formula mentioned earlier, we can calculate the margin of error:

Margin of Error = 1.96 * 0.0174 ≈ 0.034

Step 5: Interpret the margin of error.

The margin of error represents the range within which the true population proportion is likely to fall. In this example, the margin of error is approximately 0.034. This means that if we repeated the survey multiple times, we would expect the true proportion of individuals supporting the candidate to be within 0.034 of our estimated proportion (0.5625) with 95% confidence.

Please note that this is just an example of calculating the margin of error for a sample proportion. The specific formula and calculations may vary depending on the type of estimate you are trying to calculate (e.g., mean, difference in proportions, etc.) and any assumptions made in the analysis.