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Questions and Comments

Updated Review Shaobo Fang:

Now the format issue is gone and the slecture looks great!

The mathmatical derivation is clear, thorough and in details, which is extremely impressive.

To offer the readers a better technical background, the author first explained the general Maximum Likelihood Ratio test given 'c' classes.

Author first investigated over the expected value of MLE estimate based on standard deviation and expected deviation. The case of maximum likelihood estimation examples for Gaussian R.V. both $ \mu $ and $ \sigma $ unknown was investigated and is truely interesting since in real world even if the data come in with Gaussian distribution the parameter is probably still unknown. Biasness of an estimator was also briefly investigaed at the very end.

Could have been improved: It would be better for the reader if more context would be there to provide better transition regarding different parts.

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