Calculate confidence intervals for statistical analysis and research with our AI-powered tool.
Based on your input data, here are the results:
A confidence interval is a range of values used to estimate the true population parameter, based on a sample. It expresses how certain we are that a population parameter lies within that range.
For example, a 95% confidence interval means that if we were to take 100 different samples and compute a confidence interval for each sample, we would expect about 95 of the intervals to contain the true population parameter.
Enter your sample mean, standard deviation, sample size, and select a confidence level (e.g., 95%). The calculator will return the confidence interval and margin of error.
Sample Mean (x̄): The average value of your sample data.
Standard Deviation (σ or s): The measure of dispersion in your data. Use population standard deviation (σ) if known, otherwise use sample standard deviation (s).
Sample Size (n): The number of observations in your sample.
Confidence Level: The probability that the confidence interval contains the true population parameter (typically 90%, 95%, or 99%).
Confidence intervals are essential in statistics and scientific research. They help quantify uncertainty and are used in everything from clinical trials to opinion polling.
Unlike a single-point estimate, confidence intervals provide a range that is likely to contain the population parameter, giving a more complete picture of the estimate's reliability.
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