Maximum likelihood estimation is used to estimate population mean and variance. However, we can do it with sample variance too and sample variance is unbiased also. Then why we prefer maximum likelihood approach over sample variance?
It has wider applicability; used when the data distribution not known or the assumptions of normality not confirmed. It is more precise in case of the large sample size.
, have you read yourself the bullshit copied from ChatGPT? It is your aim to increase confusion and to spread nonsense? If you are not able to judge the answers of LLMs for their correctness, then PLEASE do not use them, at least don't post that crap here. Thanks.