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: Confidence intervals provide more information than point estimates. By establishing a 95% confidence interval using the sample's mean and standard deviation, and assuming a normal distribution as represented by the bell curve, the researchers arrive at an upper and lower bound that contains the true mean 95% of the time. Assume the interval is between 72 inches and 76 inches. If the researchers take 100 random samples from the population of high school basketball players as a whole, the mean should fall between 72 and 76 inches in 95 of those samples. If the researchers want even greater confidence, they can expand the interval to 99% confidence. 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.