Maximum likelihood estimators (MLEs) - I2 Inference part 3/3

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Maximum likelihood estimators (MLEs) are statistics obtained by maximizing the likelihood. MLEs are derived, shown graphically, and obtained numerically for binomial and normal models

I2 - Likelihood:

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Chapters:
00:00 Introduction
00:30 Maximum likelihood estimator (MLE)
01:40 Binomial MLE - derivation
03:35 Binomial MLE - graphically
04:20 Binomial MLE - numerical maximization
06:40 Normal MLE - derivation
08:01 Normal MLE - numerical maximization
09:15 Normal MLE - graphically
09:46 Summary
  1. Jarad Niemi
  2. probability
  3. statistics
  4. data science
  5. education
  6. likelihood
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What is the reason for using the "small y" as the "number of success" of success when we are already using "capital Y" as the script for the "random variable". Is it not confusing. What can go wrong if we use some other script.

nayanvats