Confidence Interval Calculator

A Range, Not Just a Point

A sample mean or sample proportion is always just an estimate — a different sample would give a slightly different number. A confidence interval reports a range of plausible values for the true population parameter, along with a confidence level describing how often intervals built this way actually contain the truth. A 95% confidence interval doesn't mean there's a 95% chance the true value is inside this specific interval; it means that if you repeated the sampling process many times, about 95% of the resulting intervals would contain it.

The Formulas

For a Mean (t-distribution):
CI = x̄ ± t* × (s ÷ √n)

For a Proportion (normal approximation):
CI = p̂ ± z* × √(p̂(1−p̂) ÷ n)

t* and z* are critical values pulled from the t- and standard normal distributions respectively, based on the chosen confidence level and (for the mean case) the degrees of freedom.

Worked Examples

95% confidence interval examples
ScenarioInputsResult
Meanx̄=75, s=10, n=2570.87 to 79.13
Proportion120 of 400 successes25.51% to 34.49%

In the mean example, the critical value comes from the t-distribution with 24 degrees of freedom (t* = 2.064), not the normal distribution — using z* = 1.96 instead would understate the interval's width for a sample this size.

Where This Matters

  • Clinical research — reporting the plausible range for a treatment effect, not just a single point estimate.
  • Political polling — the "margin of error" quoted in a poll defines the confidence interval around the reported percentage.
  • Manufacturing — estimating the true average dimension or defect rate of a full production run from a sample.
  • A/B testing — confidence intervals around conversion rates help judge whether an observed difference is likely real or just sampling noise.

How to Use This Calculator

  1. Choose Confidence Interval for a Mean or for a Proportion from the dropdown.
  2. For a mean: enter the sample mean, sample standard deviation, and sample size.
  3. For a proportion: enter the number of successes and the sample size.
  4. Enter your desired confidence level as a percentage (95 is the most common choice).
  5. Select Calculate to get the interval.

Related Calculations

This calculator relies on the Standard Error Calculator's underlying logic. To determine the sample size needed to hit a target margin before you collect data, use the Sample Size Calculator.