Question

Is there any example that MLE is used to estimate the sample mean (please give one if there is)? Usually I only see MLE is used to estimate sample proportion p to maximize some probability?

Does MLE only need one random sample to estimate the parameter while bootstrapping you can take many random samples as you want? What is the difference between these two methods?

Answer 1

For example, consider $N(\mu,\sigma^{2})$ , here MLE is used to estimate both the same mean $(\mu)$ and variance.

(o

Yes parameter can be estimated by using just one random sample when using the method MLE.

MLE is a method of estimation using the likelihood of the density that might have generated the sample. We find the density which is most likely to have generated the sample.

Bootstrapping estimation is based on the idea of repeated sampling to estimate the parameters of the population.