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I read in one of the statistical websites saying:

"The best estimate for p (probability of obtaining heads) from any one sample is clearly going to be the proportion of heads observed in that sample". i can generalize this saying:

"The best estimate for the population mean will always be the sample mean".

How can i come to this conclusion? any thread for this please?

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Thanks.. any proof for this. Are you saying we can differentiate the binomial function to see which value of p gives me the maximum likelihood?

i perceive that for models where the parameters are huge in number or when the degree of those parameters increase, we cant conclude in that way.
Hi Surya ,
How are you?

This is Ram from Bangalore..
It depends how you define "best". If you want a robust estimator and your data has some very extreme outliers, than the sample mean is NOT a good estimator of the population mean.


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