I'm struggling with the difference between confidence interval and expanded uncertainty.

I understand a confidence interval around the mean. For example, a 95% confidence interval around the mean says that if N samples were taken 100 times and a confidence interval was recalculated each time, at least 95 of my confidence intervals would actually contain the true mean.

The expanded uncertainty is X +/- k*s, where:

- X is my best estimate determination of the parameter of interest
- k is my coverage factor, e.g., 2 for 95%
- s is my combined standard uncertainty of X

I have scoured the internet with things like "expanded uncertainty vs. confidence interval" and can't find much.

Thanks for your help.