Sample Size Calculator
Determine the optimal sample size for your survey or research study with our advanced calculator featuring confidence intervals and margin of error analysis.
Sample Size Parameters
Calculating your sample size…
Sample Size Calculation Results
Understanding Your Results
Sample Size is the number of observations or responses needed to achieve your desired level of confidence and margin of error.
Adjusted Sample Size accounts for your expected response rate. If you expect only 60% of people to respond, you’ll need to contact more people to get your required sample size.
Confidence Interval indicates the range within which the true population parameter is likely to fall. A 95% confidence level with a 5% margin of error means that if you repeated your study 100 times, 95 of those times the results would fall within this range.
Standard Error measures the variability of the sample mean. A smaller standard error indicates a more precise estimate of the population parameter.
Frequently Asked Questions
Sample size is the number of observations or participants included in a study. It’s important because it affects the accuracy, reliability, and generalizability of your results. A sample that’s too small may not accurately represent the population, while a sample that’s too large may waste resources without providing additional benefit.
The confidence level depends on your research goals and the consequences of being wrong. For most research, a 95% confidence level is standard. For medical studies where errors can have serious consequences, a 99% confidence level might be appropriate. For less critical studies, a 90% confidence level might be sufficient.
Margin of error is the maximum expected difference between the true population parameter and a sample estimate. A smaller margin of error requires a larger sample size. For example, reducing the margin of error from 5% to 3% can significantly increase the required sample size.
50% is used as the default because it represents maximum variability. When you don’t know the actual response distribution, using 50% ensures your sample size will be large enough for any possible distribution. If you have prior knowledge that the response distribution is different (e.g., 80% or 20%), you can use that value for a more precise sample size calculation.
If you expect a response rate less than 100%, you need to adjust your sample size by dividing the required sample size by the expected response rate. For example, if you need 385 responses but expect only a 60% response rate, you should contact 385 ÷ 0.60 = 642 people to get your required sample size.