A nice answer says
A margin of error and a confidence interval are pretty much the same thing - it's the interval in which you are quite confident that the true parameter lies. If you have a 95% confidence interval, that means that if you were to repeat your experiment, 95% of the time the true parameter value would fall within your interval. Roughly speaking, there's a 95% chance that the interval contains the true value. The margin of error is simply describing the width of your confidence interval. So, if you have a confidence interval of [4, 6], you can say that your parameter estimate is 5 with a margin of error of 1.
where the term "true parameter" is used.
I am trying to understand that term. I searched a bit and got a post What, precisely, is a confidence interval?, which seems to talk about CI theoretically without a real life example, which is hard for me to understand.
Assume the U.S. Census Bureau published a survey of people in poverty in 1995. The survey stated a confidence level of 90% for the statistics “The number of people in poverty in the United States is 35,534,124 to 37,315,094.”
What the "true parameter" is in the example of Census Bureau's survey? Could someone please give a hint?
The example is adapted from source