Blogs

Getting reliable K in K means clustering

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

Bootstrapping, Monte Carlo and all that… — Part2

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

Beginning with R — The uncharted territory Part 2

Second part of initial introduction to R. Topics include arrays, factors and dataframes.

Beginning with R — The uncharted territory Part 1

Initial introduction to R. Topics include data types, data structures such as named lists, vectors and matrices.

Bootstrapping, Monte Carlo and all that… — Part1

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.