Comparison of Two Populations

A short compilation of visual methods for comparing two samples.

Visual Tools

  1. Box Plots
  2. Bee Swarm Plots
  3. Violin Plots
  4. Histograms
  5. Kernel Density Estimation
  6. Empirical ROC
  7. Empirical Cumulative Distribution Functions

Hypothesis Tests

  1. Kolmogorov-Smirnov
  2. Anderson-Darling

You can find the Python code below or in this Git Link.


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View this gist on GitHub

2 thoughts on “Comparison of Two Populations”

  1. […] Nowadays, more than 40 years after their official introduction,  Box plots are still widely used in academia as well as across all kinds of industries. They have demonstrated to be useful for revealing the central tendency and variability of the data, the distribution (symmetry or skewness) shape, and the possible presence of outliers. Moreover, they are also a powerful graphical technique for comparing samples from two or more different populations (as we observed in previous post Comparison of Two Populations). […]

  2. For the empirical ROC, the value of the AUC is relevant in any way to determine if the two sample come from the same distribution? Which of those methods can be generalized to compare more than two samples?

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