Instead of finding K in K means clustering through visualization, let us find K mathematically.

Second part of bootstrapping and monte carlo. Applying the theory through python and practical examples

Extracting relevant results from a particular dataset requires a rigorous understanding of its statistical properties - mainly the type of distribution the data possesses. For some underlying statistical distribution in the data, parametric tests are applied to infer statistical properties of a particular estimator. It may also happen that the data does not possess any specific statistical distribution in which case, nonparametric tests are applied.
In statistical paradigm, we define an estimator to be a rule to conclude statistic of some unknown parameter from the data.

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