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: A confidence interval, in statistics, refers to the probability that a population parameter will fall between a set of values for a certain proportion of times. Key Takeaways
A confidence interval displays the probability that a parameter will fall between a pair of values around the mean. Confidence intervals measure the degree of uncertainty or certainty in a sampling method. They are most often constructed using confidence levels of 95% or 99%. Understanding Confidence Interval
Confidence intervals measure the degree of uncertainty or certainty in a sampling method. 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;