I wrapped up my undergraduate statistics degree recently and am about to start a stats heavy role as my first job. I've been brushing up on my frequentist knowledge and I'm currently trying to find a simple way of interpreting a confidence interval (say for the mean of the sampling distribution for convinience). Wikipedia says the following:
"For example, out of all intervals computed at the 95% level, 95% of them should contain the parameter's true value."
I know this is not the same as saying "the true parameter belongs to the interval with probability 0.95", but practically what does this mean to us? It feels like an a practical scenario we would just assume that the parameter should be in the interval with 95% probability.
