A New Interactive Approach to Learning Data Analysis

Python implementation of an extension of the Kolmogorov-Smirnov test for multivariate samples

about statistical techniques for Data Science

Very large scale classification based on K-Means clustering & Multi-Kernel SVM(SimpleMKL), Soft Computing article, June 2019, https://dl.acm.org/doi/abs/10.1007/s00500-018-3041-0

XeroGraph is a Python package developed for researchers and data scientists to analyze, visualize and impute missing data in datasets.

Testing a self implemented LCG vs. C# standard through the Kolmogorow Smirnow test & and a Runs Test

A simple, vectorized implementation of the two-sample Kolmogorov-Smirnov test in PyTorch.

Matlab implementation of the improved Peacock algorithm by Yuanhui Xiao.

R functions mainly for computations related to Kolmogorov-Smirnov tests

This is a homework I did in the Spring 2017. It involves conducting Chi Square Tests, Confidence Intervals, Kolmogorov-Smirnov Tests, and Shapiro-Wilk Normality Tests. It has problem numbers that are associated to problems in "Using R: Introductory Statistics".

Code for fitting EEG data with Wishart and t-Wishart distributions

The salary dataset contains info on 474 Midwestern bank employees. Tasks include understanding the dataset's structure, summarizing numerical variables, testing hypotheses on salary equality, gender-based differences, age group analysis, and proportion comparison.

ICG (Inversive Congruential Generator), MSM (Middle Square Method), LFG (Lagged Fibonacci Generator), MRG (Multiple Recursive Generators), KS Test (Kolmogorov-Smirnov Test)

ClusterTrack software allowed for the first time comprehensive measurements of microtubule behavior, including during stages of depolymerization, for which there is no known molecular marker