Confidence Level
The expected frequency with which an estimated interval will contain the true population parameter if the study were repeated multiple times.
What is Confidence Level?
The confidence level dictates the width of a confidence interval. It means that if researchers were to draw infinite samples and construct intervals in the exact same way, 95% of those calculated intervals would successfully capture the true population parameter.
Why Confidence Level Matters
It provides a transparent framework for expressing the uncertainty and precision of sample estimates, moving beyond binary significant or not thinking.
Example
A political poll reports a candidate's support at 45% with a 95% confidence level. This means the pollsters are using a method that, over the long run, correctly brackets the true public sentiment 95% of the time.
Common Mistakes
- Believing that a specific 95% confidence interval has a 95% probability of containing the true parameter.
- Assuming that a higher confidence level yields a more precise (narrower) interval; it actually requires a wider interval.