Enter the Population
Provide the total number of people or observations in the group you want your research to represent.
Research Planning Tool
Sample Size Calculator
Determine how many survey responses or research participants you need using your population size, confidence level, margin of error, response distribution, design effect, and expected response rate.
Research Parameters
Enter your study requirements to calculate the recommended sample.
Calculation Results
Your recommended sample and recruitment targets.
Recommended sample size
370
Completed responses needed for your selected criteria.
Invitations needed
617
Population coverage
3.70%
Initial sample
385
Design-adjusted
370
Study summary
For a population of 10,000, you need at least 370 completed responses at a 95% confidence level and 5% margin of error.
Formula used
n₀ = Z² × p(1-p) ÷ e²
n = n₀ ÷ [1 + ((n₀ - 1) ÷ N)]
Instant Calculation
Results update without reloading the page.
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Your research inputs remain in your browser.
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Use the calculator on phones, tablets, and desktops.
Research Focused
Supports surveys, polls, studies, and experiments.
How It Works
Calculate Your Sample in Three Steps
Use statistically relevant inputs to estimate the number of completed responses required for dependable research results.
Select Your Precision
Choose a confidence level, margin of error, expected distribution, and any appropriate survey design adjustment.
Review the Result
See the recommended completed sample, recruitment target, population coverage, and a plain-language study summary.
What Is a Sample Size Calculator?
A sample size calculator estimates how many participants, survey responses, measurements, or observations you need to represent a larger population with a chosen level of statistical confidence.
Collecting data from every member of a population is often expensive, slow, or impossible. A carefully selected sample lets researchers study a manageable group and use the findings to make conclusions about the complete population.
Important Sample Size Factors
- Population size: The total number of people or items included in your target group.
- Confidence level: How certain you want to be that the population result falls within your selected range.
- Margin of error: The acceptable difference between the sample estimate and the true population value.
- Response distribution: The expected proportion of the population with a particular response or characteristic.
- Design effect: An adjustment that accounts for complex sampling methods that may be less efficient than simple random sampling.
- Response rate: The percentage of invited people expected to complete the survey or study.
Why 50% Is Commonly Used
When you do not know the expected proportion, using a 50% response distribution is the safest choice. It produces the maximum variability and usually results in the largest required sample size.
Finite Population Correction
When your population is limited and known, the finite population correction reduces the required sample. This prevents you from collecting more responses than necessary while preserving the selected confidence level and margin of error.
Practical recommendation: A 95% confidence level, 5%
margin of error, and 50% response distribution are common starting
points for general surveys. Your field, study design, and analysis
method may require different settings.
Frequently Asked Questions
Sample Size Calculator FAQs
Understand the most important concepts before planning your survey, research study, or data collection project.
A sample size is the number of people, responses, observations, or
measurements included in a study. It should be large enough to represent
the target population with an acceptable level of precision.
A 95% confidence level is the most common choice for general surveys
and research. A 90% level may be suitable for exploratory research,
while 99% is used when greater certainty is required.
A 5% margin of error is widely used for general research. A 3% or 2%
margin provides greater precision but requires a much larger sample.
The acceptable margin depends on the purpose and importance of the study.
Use 50% when you do not have a reliable estimate from previous research.
It produces the most conservative sample size because variability is
highest when the expected proportion is evenly divided.
Sample size is the number of completed responses you need. Response rate
is the percentage of invited participants who are expected to respond.
A lower response rate means you must invite more people.
Design effect adjusts the sample size for complex sampling methods such
as cluster sampling. A value of 1 represents simple random sampling.
Values above 1 increase the required sample to account for reduced
statistical efficiency.
No. After the population becomes sufficiently large, the required sample
changes only slightly. Confidence level, margin of error, and response
distribution usually have a stronger effect on the result.
Yes, it can provide a planning estimate for surveys and proportion-based
studies. However, advanced studies involving multiple groups, regression,
hypothesis testing, rare outcomes, or statistical power analysis may
require a specialized method.
Important: This calculator estimates sample size for a
population proportion. It does not replace a formal power analysis or advice
from a qualified statistician for clinical, scientific, legal, or high-risk
research.