Calculate confidence intervals for your sample data instantly. No signup required.
Your Confidence Interval:
(, )
Margin of Error
±
Z-Score Used
A confidence interval is a range of values that likely contains the true population parameter you're trying to estimate. When you collect sample data, you can't know the exact population mean, but a confidence interval gives you a range where the true mean probably falls.
For example, a 95% confidence interval means that if you repeated your sampling process 100 times, about 95 of those intervals would contain the true population mean.
The width of your confidence interval depends on three factors: your sample size (larger samples = narrower intervals), your data's variability (lower standard deviation = narrower intervals), and your chosen confidence level (higher confidence = wider intervals).
CI = x̄ ± z × (σ / √n)
Where:
Now that you know how to calculate confidence intervals, create a survey to collect the data. Try it yourself 👇
95% is the most common choice in research and surveys. Use 99% when you need extra certainty (like medical research), or 90% when you can tolerate more uncertainty and want a narrower interval.
Generally, sample sizes of 30 or more work well when your data is roughly normally distributed. Larger samples give you narrower (more precise) confidence intervals.
The margin of error is half the width of the confidence interval. It's the "plus or minus" value you add and subtract from your sample mean to get the interval bounds.
This calculator uses z-scores, which are appropriate when you know the population standard deviation or have a sample size of 30 or more. For smaller samples with unknown population standard deviation, a t-score might be more appropriate.
Standard deviation measures the spread of your data. Most spreadsheet tools (Excel, Google Sheets) have built-in functions: use STDEV.S for sample standard deviation or STDEV.P for population standard deviation.
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