I am following a video lecture on Statistics, which introduces the concept of confidence intervals in the following way:
"A bank vice president is interested in the average checking account balance for all personal accounts. A random sample of 500 accounts is selected, and the average is calculated. What level of "confidence" for the mean will the VP be satisfied with?"
What I don't understand is, why are confidence intervals even necessary? I learned previously that the mean of the sampling distribution of the sample mean is exactly equal to the population mean. So, wouldn't it be better for the VP to do that i.e. take many samples and calculate the mean of the sampling distribution of the sample mean (and thus get the exact population mean), instead of just using one sample to calculate confidence intervals (which will not give you the exact population mean)?
(Question source: https://www.youtube.com/watch?v=9GtaIHFuEZU)