Sample Size Calculator

Determine exactly how many survey responses or observations you need to achieve statistically significant results. Enter your acceptable margin of error and confidence level to calculate your ideal sample size.

How to use this calculator

1. Margin of Error: The maximum amount of error you are willing to accept. If your survey finds that 60% of people like a product, a 5% margin of error means the true number is likely between 55% and 65%. (Default: 5%).
2. Confidence Level: How confident you want to be that the true population parameter falls within your margin of error. (Default: 95%).
3. Estimated Proportion: Your expected result. If you have no idea what the result will be, leave this at 50%. This represents the most conservative estimate and ensures your sample size will be large enough regardless of the final outcome.
4. Population Size (Optional): If you are surveying a massive or unknown population (like “all adults in India”), leave this blank. If you are surveying a specific, small group (like a 400-person graduating class), enter the number to apply a finite population correction, which may reduce the number of responses you need.

Understanding Your Results

When you can’t survey every single person in a population, you have to take a sample. But if your sample is too small, your results will be heavily influenced by random chance.

• Required Sample Size: The absolute minimum number of valid responses you need to collect. Since you cannot survey a fraction of a person, this number is always rounded up to the next whole number.
• The 50% Rule: The closer a proportion gets to 50/50, the larger the sample size you need to be confident in the result. If you expect a result to be extremely lopsided (e.g., 90% vs 10%), you actually need fewer people to prove it. When in doubt, assuming 50% guarantees your sample size is large enough.