Sample Size & Margin of Error Calculator

Calculate statistically significant sample sizes for surveys, market research, and academic experiments using Cochran’s formula with 90%, 95%, and 99% confidence levels.

Input Parameters
Calculation Result
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Enter values to see real-time calculation.
⚖ Disclaimer: Results and formulas are estimates for informational and educational purposes only. They do not constitute certified tax, legal, or financial advice. Legal Disclaimer →

How to Use the Sample Size & Margin of Error Calculator

  1. Enter your total target population size (or leave large for infinite population).
  2. Select your desired Confidence Level (90%, 95%, or 99%).
  3. Enter your acceptable Margin of Error percentage (e.g. ±5%).
  4. The calculator computes the exact number of survey respondents required.

Key Features & Capabilities

  • Cochran’s statistical sample size formula with Finite Population Correction (FPC).
  • Supports 90%, 95%, and 99% critical Z-score confidence levels.
  • Essential for market researchers, UX testers, and academic researchers.

Technical Architecture & Privacy

Sample Size & Margin of Error Calculator is engineered with a focus on performance, mathematical accuracy, and maximum user privacy. Operating entirely in-browser on the client side, all processing takes place locally within your browser's JavaScript engine. None of your financial numbers, text entries, or private inputs are ever transmitted to or stored on remote servers.

Frequently Asked Questions

What is a standard sample size for a survey? ▾

For large populations (over 100,000), a sample size of 384 respondents provides a 95% confidence level with a ±5% margin of error.

What does margin of error mean? ▾

Margin of error indicates how closely survey results reflect the views of the entire population. A 5% margin of error means results will be within 5 percentage points of the true population value.

🔗 Embed this Tool on your Website

Embed this responsive tool into your website, blog, or documentation. It runs in a 100% isolated sandbox with automatic height resizing.