Determine the minimum number of respondents needed for your research study.
Total group size you're studying (leave blank for infinite)
80%
85%
90%
95%
99%
Recommended Sample Size:
0
Based on your parameters for statistical significance.
How to Determine Sample Size for Research
Determining the correct sample size is a critical step in any statistical study or market research. If your sample size is too small, you may not get statistically significant results. If it is too large, you might waste time and resources.
Understanding the Variables
Population Size: The total number of people in the group you are trying to study. If you are surveying a whole city, this is the city's population. If the population is extremely large or unknown, we treat it as "infinite."
Confidence Level: How confident you want to be that the actual population reflects your survey results. A 95% confidence level is the industry standard.
Margin of Error: Also known as the confidence interval. This is the amount of "wiggle room" you allow. A 5% margin of error means if 60% of your sample picks an answer, you can be sure that between 55% and 65% of the total population would have picked that answer.
Population Proportion: This represents the expected distribution of answers. Usually, 50% is used because it is the most conservative estimate and ensures the largest required sample size.
Common Z-Scores for Confidence Levels
Confidence Level
Z-Score
90%
1.645
95%
1.96
99%
2.576
Example Calculation
Suppose you want to survey a company of 1,000 employees. You want a 95% confidence level and a 5% margin of error. Using the finite population correction formula, the calculator will determine that you need a sample size of approximately 278 employees to obtain valid data.
function calculateSampleSize() {
var N = parseFloat(document.getElementById('popSize').value);
var Z = parseFloat(document.getElementById('confLevel').value);
var e = parseFloat(document.getElementById('marginError').value) / 100;
var p = parseFloat(document.getElementById('popProp').value) / 100;
// Validation
if (isNaN(e) || e = 1) {
alert("Please enter a valid Margin of Error (e.g., 5 for 5%)");
return;
}
if (isNaN(p) || p = 1) {
alert("Please enter a valid Population Proportion (e.g., 50 for 50%)");
return;
}
var n0; // Sample size for infinite population
var finalN;
// Step 1: Calculate infinite population sample size (Cochran's Formula)
// n0 = (Z^2 * p * (1-p)) / e^2
n0 = (Math.pow(Z, 2) * p * (1 – p)) / Math.pow(e, 2);
// Step 2: Adjust for finite population if N is provided
if (!isNaN(N) && N > 0) {
// n = n0 / (1 + (n0 – 1) / N)
finalN = n0 / (1 + ((n0 – 1) / N));
} else {
finalN = n0;
}
// Round up because you can't have a fraction of a respondent
var result = Math.ceil(finalN);
// Display results
document.getElementById('sampleResult').innerHTML = result.toLocaleString();
document.getElementById('resultContainer').style.display = 'block';
if (!isNaN(N) && N > 0) {
document.getElementById('calcLogicDesc').innerHTML = "Based on a population of " + N.toLocaleString() + ", " + (p*100) + "% proportion, and " + (e*100) + "% margin of error.";
} else {
document.getElementById('calcLogicDesc').innerHTML = "Based on an infinite population, " + (p*100) + "% proportion, and " + (e*100) + "% margin of error.";
}
}