Why don’t we calculate the average of an entire given population instead of computing confidence interval to estimate the population mean? We compute confidence intervals to estimate the true population mean of either a sample (when population standard deviation is unknown) or an entire population (when population standard deviation is known). But I wonder why, if we are given an entire population, why don't we calculate the average of that population instead of computing confidence interval to estimate the population mean since we already have the entire population? I'm not a Math or Stat major so I apologize if my question does not sound "smart".

If we're able to observe the entire population of interest then that's exactly what we'd do!  In this case we don't require any statistical inference because we directly observe the entire population of interest.  Where statistical inference (including confidence intervals, etc.) comes in is when, for some reason, we are unable to observe the entire population.  Often this is because it is too expensive or inconvenient to sample then entire population, but in some cases it might be completely infeasible.
