Confidence Intervals

Confidence intervals provide a range of values that are likely to contain the true value of a population parameter, such as a mean or proportion. They are calculated from sample data and are associated with a confidence level, indicating the probability that the interval captures the true parameter. A wider interval suggests more uncertainty, while a narrower interval suggests more precision in estimating the parameter. A 95% confidence interval, for example, means that if the same sampling method were repeated many times, 95% of the calculated intervals would contain the true population parameter.

Visit the following resources to learn more:

• @article@What Is a Confidence Interval and How Do You Calculate It?
• @article@Confidence interval