Free online margin of error calculator. Calculate confidence intervals for survey data. Supports 90%, 95%, 99% confidence levels. Perfect for students, researchers, and data analysts.
Number of respondents or observations in your sample
Proportion of respondents with the characteristic (0–1). Defaults to 0.5 for maximum margin of error.
How confident you want to be that the true value falls within the interval
Total population size. Leave blank if unknown or very large (assumes infinite population).
This calculator computes the margin of error and confidence interval for survey data using the standard formula. It supports finite population correction for when your sample is a significant fraction of the total population. The margin of error tells you how far the sample proportion might deviate from the true population proportion at a given confidence level. Widely used in polling, market research, social science, and quality assurance.
Margin of error (MoE) is the maximum likely distance between a sample statistic and the true population parameter. It quantifies the uncertainty in survey results. For example, if 52% of respondents support a candidate with a ±3% margin of error, the true support is likely between 49% and 55%.
95% is the standard in most research and polling. Use 90% for exploratory studies where you want narrower intervals. Use 99% for critical decisions where you need higher certainty. Higher confidence means a wider (less precise) interval.
Use FPC when your sample is more than 5% of the total population. For example, if surveying 200 employees out of 500 total, FPC will reduce the margin of error. For large populations (n/N < 0.05), FPC has negligible effect and can be ignored.
A proportion of 0.5 gives the maximum possible margin of error for a given sample size. When planning a survey and you do not know the expected proportion, using 0.5 ensures your sample size is large enough for the worst-case scenario.