Optimum sample size for a large population? I am trying to identify what should be the optimum sample for a population. Based on various articles. I identified that there is a formula that helps to calculate that , based on Confidence Level, Confidence Interval and variance.
However, what I is confusing is that for a set value of Confidence Level, Confidence Interval and variance,  we get the same sample size irrespective of the population size after a certain point based on the formula.
Could anyone kindly let me know if I am understanding it correctly or not. Also, how does the population size have no effect on the sample size after a certain point? 

The calculations you're reading assume an infinite population, sometimes called a data-generating process (DGP), though this term is a bit loose. The gist is that a DGP can be sampled from as many times as one wants, such as flipping a coin over and over and over and over. In this case, "population" is a convenient way to represent to newcomers the idea of a distribution in mathematics.
There are, however, results for finite-size populations, though I would consider such a case to be the exception in most areas of statistics (certainly in what I do).
