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Confidence Interval Calculator

Calculate a two-sided interval for a population mean or proportion with transparent assumptions.

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Complete guide

Confidence interval calculator for a mean or proportion

Choose mean or proportion, enter sample information and confidence level. Calculator24 returns lower and upper limits, estimate, standard error, margin and method.

Editorial checkMean standard-error formula checked against NIST; proportion interval uses the Wilson score construction.Updated September 10, 2026
An interval surrounds a sample estimateHigher confidence widens the interval; larger samples usually narrow it through the square-root term.1Lower limit2Point estimate3Upper limit
An interval surrounds a sample estimateHigher confidence widens the interval; larger samples usually narrow it through the square-root term.

What confidence means

Confidence describes the long-run performance of the interval procedure. A 95% method would contain the true parameter in about 95% of repeated samples under its assumptions.

Interval for a mean

When population standard deviation is unknown, use sample standard deviation and a t critical value with n−1 degrees of freedom.

x̄±t*·s/√n

Interval for a proportion

The Wilson score interval stays within zero and one and behaves better than the simple p̂±z standard-error interval near boundaries.

Worked mean example

For x̄=50, s=10 and n=100, standard error is 1 and the 95% t multiplier is just under 2, giving limits near 48 and 52.

Width and sample size

Standard error shrinks with √n, so quadrupling sample size roughly halves the random-error component when other inputs remain fixed.

Interpretation limits

The interval does not repair selection bias, measurement error, dependence or an invalid sampling frame. It also does not assign a probability to a fixed parameter after the data are observed.

What changes interval width

Effects assume other inputs remain fixed.
ChangeTypical effect
Higher confidenceWider
Larger sampleNarrower
More variabilityWider
BiasNot repaired by width

Frequently asked questions

Is there a 95% chance the parameter is inside?

In frequentist terms, 95% describes the long-run success rate of the method, not a probability assigned to the fixed parameter.

Why use t for a mean?

The population standard deviation is usually unknown and estimated from the sample.

Why use Wilson for a proportion?

It behaves better near zero or one than the basic symmetric normal interval.

Can confidence limits exceed the data range?

Mean intervals can; proportion limits are constrained to 0–100%.

Does a narrow interval prove accuracy?

No. Systematic bias can remain.

How does sample size affect width?

The random-error term usually scales approximately with one over the square root of n.

What to keep in mind

The mean interval uses a t critical approximation and assumes independent observations from an approximately normal population or an adequate sample. The proportion interval is Wilson; sampling design and bias are outside scope.

Results display up to 8 decimal places; exported numbers preserve calculation precision. This is a calculation summary, not an official certificate.

Sources and references

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