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: Doing so invariably creates a broader range, as it makes room for a greater number of sample means. If they establish the 99% confidence interval as being between 70 inches and 78 inches, they can expect 99 of 100 samples evaluated to contain a mean value between these numbers. A 90% confidence level, on the other hand, implies that we would expect 90% of the interval estimates to include the population parameter, and so forth. Frequently Asked Questions
What Does a Confidence Interval Reveal? 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. How Are Confidence Intervals Used? 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 where some intervals include the true population parameter and others do not.