This project implements in Python some common statistical analysis methods used in data analysis, including Entropy, Mutual Information, Kolmogorov–Smirnov test, Kullback-Leibler divergence (KLD), AB tests (Mann-Whitney U and t-tests)

A basic report and code to apply Kolmogorov Smirnov tests on a given set of data using Jupyter Notebook.

A natural time analysis of the Earthquake Cycles in Taiwan by evaluating EPS scores using R and Python.

The PKS Test software was designed to directly verify whether a phylogeny is clock-like following a Poisson law.

Probability and Statistics for Data Scientist - Course Project. Various Testing(Hypothesis, T-Test, Z-Test, KS Test etc) are performed on Covid and crime dataset for Los Angeles. Auto Regression and Linear Regression are also performed without using scimitar libraries in python.

A system for monitoring statistical data distribution shifts in distributed settings

A Hemispherical Comparison code using HEALPiX and Kolmogorov–Smirnov test for probing isotropy

Applied KS test and T-test to check whether rental subsidy rate’s distributions are different across different PHAs and implemented Pearson-correlation analysis to explore the linear correlation between rental subsidy rate and other factors.