Title: Confidence Interval Definition
Headings: Confidence Interval
Confidence Interval
What Is Confidence Interval?
Key Takeaways
Understanding Confidence Interval
Calculating Confidence Interval
Frequently Asked Questions
What Does a Confidence Interval Reveal?
How Are Confidence Intervals Used?
What's a Common Misconception About Confidence Intervals?
What Is a T-test?

Content: They can take any number of probability limits, with the most common being a 95% or 99% confidence level. Confidence intervals are conducted using statistical methods, such as a t-test . Statisticians use confidence intervals to measure uncertainty in a sample variable. For example, a researcher selects different samples randomly from the same population and computes a confidence interval for each sample to see how it may represent the true value of the population variable. The resulting datasets are all different; some intervals include the true population parameter and others do not. A confidence interval is a range of values, bounded above and below the statistic's mean, that likely would contain an unknown population parameter. Confidence level refers to the percentage of probability, or certainty, that the confidence interval would contain the true population parameter when you draw a random sample many times. Or, in the vernacular, "we are 99% certain ( confidence level) that most of these samples (confidence intervals) contain the true population parameter." The biggest misconception regarding confidence intervals is that they represent the percentage of data from a given sample that falls between the upper and lower bounds.