Confidence Interval Calculator

Understanding Confidence Intervals

A confidence interval in statistics indicates a range within which the true population parameter is likely to fall. It's calculated from sample data and provides a level of certainty (confidence level) that the true parameter lies within the interval.

For a population proportion, the confidence interval is estimated using the sample proportion, sample size, and desired confidence level. The formula involves calculating a margin of error which is then added and subtracted from the sample proportion to establish the interval's upper and lower bounds.

For example, a 95% confidence interval means that if we were to take many samples and calculate confidence intervals for each sample, about 95% of these intervals would contain the true population proportion.

Key terms:

• Successes: The number of successful outcomes in your sample.
• Sample Size: The total number of observations in your sample.
• Confidence Level: The probability that the confidence interval contains the true population parameter.
• Lower Bound & Upper Bound: The lower and upper limits of the confidence interval.

Learn more about confidence intervals on resources like Khan Academy or Wikipedia.