Title: Understanding Confidence Intervals | Easy Examples & Formulas
Headings: Confidence intervals explained
Confidence intervals explained
What exactly is a confidence interval?
Confidence level = 1 − a
When do you use confidence intervals?
Calculating a confidence interval: what you need to know
Point estimate
Finding the critical value
Finding the standard deviation
Sample size
What can proofreading do for your paper?
Confidence interval for the mean of normally-distributed data
Confidence interval for proportions
Confidence interval for non-normally distributed data
Reporting confidence intervals
Caution when using confidence intervals
Frequently asked questions about confidence intervals
What is the difference between a confidence interval and a confidence level?
How do you calculate a confidence interval?
What is a standard normal distribution?
What are z-scores and t-scores?
What is a critical value?
What does it mean if my confidence interval includes zero?
How do I calculate a confidence interval if my data are not normally distributed?
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Rebecca Bevans

Content: Understanding Confidence Intervals | Easy Examples & Formulas
Confidence intervals explained
Published on  August 7, 2020  by Rebecca Bevans. Revised on  February 11, 2021. When you make an estimate in statistics, whether it is a summary statistic or a test statistic, there is always uncertainty around that estimate because the number is based on a sample of the population you are studying. The confidence interval is the range of values that you expect your estimate to fall between a certain percentage of the time if you run your experiment again or re-sample the population in the same way. The confidence level is the percentage of times you expect to reproduce an estimate between the upper and lower bounds of the confidence interval, and is set by the alpha value. What exactly is a confidence interval? A confidence interval is the mean of your estimate plus and minus the variation in that estimate. This is the range of values you expect your estimate to fall between if you redo your test, within a certain level of confidence. Confidence, in statistics, is another way to describe probability. For example, if you construct a confidence interval with a 95% confidence level, you are confident that 95 out of 100 times the estimate will fall between the upper and lower values specified by the confidence interval.