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Margin of Error Calculator

Use the Margin of Error Calculator. Enter Sample proportion (%) and Sample size for a clear result, formula explanation, and practical planning checks.

Margin of Error measurements

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Result

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How to calculate margin of error

This calculator finds the margin of error for a survey or poll based on sample proportion and sample size — the range within which the true population value is expected to fall, at a 95% confidence level.

How the calculation works

Margin of error = 1.96 × √((p×(1−p))÷n) × 100, where p is the sample proportion (as a decimal) and n is sample size. The 1.96 multiplier corresponds to a 95% confidence level.

Example

A sample proportion of 50% from a sample of 1,000: 1.96×√(0.5×0.5÷1,000)×100 ≈ 1.96×0.0158×100 ≈ 3.1%.

Frequently asked questions

How is Result calculated?

Result = 1.96 × sqrt(([Sample proportion] ÷ 100) × (1 − [Sample proportion] ÷ 100) ÷ [Sample size]) × 100.

Is the Margin of Error Calculator free to use?

Yes — every calculator on Simple Calculator Tools is free, runs in your browser, and does not require an account.

Quick Insight

Margin of Error Calculator

Margin of error = 1.96 × √((p×(1−p))÷n) × 100, where p is the sample proportion (as a decimal) and n is sample size. The 1.96 multiplier corresponds to a 95% confidence level.

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Your personalized explanation

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Pro Tips for Margin of Error

  1. Margin of error is largest when the sample proportion is near 50% and shrinks as it approaches 0% or 100% — this is a mathematical property of the formula, not a data quality issue.
  2. Larger sample sizes reduce margin of error, but with diminishing returns — quadrupling sample size only halves the margin of error, since the formula depends on the square root of sample size.

Common Margin of Error Mistakes to Avoid

  • Assuming margin of error is the same across every reported percentage in the same survey, when it actually varies slightly depending on how close each specific percentage is to 50%.

When to Use This Calculator

This calculator finds the margin of error for a survey or poll based on sample proportion and sample size — the range within which the true population value is expected to fall, at a 95% confidence level.

Content reviewed: August 2026 · Robert Threadgill
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