Confidence Interval Calculator

A 95% confidence interval means that if you were to repeat the experiment and collect samples over and over again, approximately 95% of those calculated intervals would contain the true population mean. It does not mean there is a 95% probability that the true mean lies in this specific calculated interval.

Use a Z-interval if you know the population standard deviation (which is rare in real studies) or if your sample size is large (typically n > 30). Use a T-interval if the population standard deviation is unknown and you are using the sample standard deviation, which is the standard procedure for small sample datasets.

Increasing the sample size decreases the standard error, which in turn narrows the confidence interval. A larger sample size provides more precision, resulting in a smaller margin of error.

The margin of error is the distance from the sample mean to either end of the confidence interval. It is calculated by multiplying the critical value (z* or t*) by the standard error of the mean.

Yes, absolutely. The standard deviation measures the spread of the data, while the mean measures the center. A high standard deviation relative to the mean simply indicates that the data points are widely scattered, which is common in volatile metrics.