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Confidence Interval Calculator

Calculate confidence intervals for population means. Toggle between 80%, 90%, 95%, 99%, and 99.9% confidence levels. Shows margin of error and Z-score used.

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Formula

CI = x-bar +/- Z * (s / sqrt(n))

A confidence interval gives a range of values likely to contain the true population mean. It uses the sample mean, standard error (s/sqrt(n)), and a Z-score that depends on the confidence level. A 95% CI uses Z = 1.96, meaning we are 95% confident the true mean falls within this range.

Worked Example

Mean: 75, Std Dev: 10, n: 50, Level: 95% SEM = 10 / sqrt(50) = 1.414 Margin = 1.96 x 1.414 = 2.772 CI = (75 - 2.772, 75 + 2.772) = (72.23, 77.77) We are 95% confident the true mean is between 72.23 and 77.77.

What Is a Confidence Interval?

A confidence interval provides a statistical estimate of a range of values within which the true population parameter, often the mean, is likely to lie. Instead of giving a single point estimate, which is almost certainly wrong, a confidence interval offers a lower and upper bound, along with a specified level of confidence. For example, a 95% confidence interval for a population mean implies that if we were to take many samples and construct an interval for each, approximately 95% of those intervals would contain the true population mean. It's crucial to understand that the confidence refers to the method or the process, not the specific interval itself. We don't say there's a 95% chance the true mean is within this particular interval, but rather that we are 95% confident that our method produced an interval that captures the true mean. This statistical tool helps researchers and analysts quantify the uncertainty associated with their sample estimates, providing a more robust understanding of population characteristics based on limited sample data. The interval's width is influenced by the sample size, the variability within the sample (standard deviation), and the chosen confidence level. A wider interval indicates more uncertainty, while a narrower one suggests greater precision.
  • Quantifies the uncertainty of a sample mean's estimate.
  • Provides a range, not a single point, for the true population mean.
  • Widely used in scientific research, quality control, and market analysis.
  • Its width is affected by sample size, standard deviation, and the confidence level.

Understanding confidence intervals is essential for making informed decisions based on sample data. Use the Calculory.AI Confidence Interval Calculator to quickly compute these vital ranges for your own datasets.

You can also calculate changes using our Standard Error Calculator or Standard Deviation Calculator.

Frequently Asked Questions

What does 95% confidence mean?

If you repeated the study many times and computed a 95% CI each time, approximately 95% of those intervals would contain the true population mean. It does NOT mean there is a 95% probability the true mean is in this specific interval.

When should I use 99% vs 95%?

95% is standard for most research. Use 99% when the consequences of being wrong are high (medical, safety). Higher confidence means wider intervals (less precise but more certain).

What is the Z-score for each confidence level?

80%: Z = 1.282, 90%: Z = 1.645, 95%: Z = 1.960, 99%: Z = 2.576, 99.9%: Z = 3.291. Higher confidence requires larger Z-scores.

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