A new development cycle of the Statistical Toolkit

TL;DR

This paper introduces an enhanced open source Statistical Toolkit designed for robust distribution comparison, supporting diverse experimental needs with new tests, improved algorithms, and user-friendly features for both small and large-scale analyses.

Contribution

The paper presents a new development cycle for the Statistical Toolkit, including additional statistical tests, improved algorithms, and a simplified user interface for broader applicability.

Findings

Added new statistical tests for one-sample problems

Enhanced algorithms increase robustness of results

User-friendly interface supports various analysis scales

Abstract

The Statistical Toolkit is an open source system specialized in the statistical comparison of distributions. It addresses requirements common to different experimental domains, such as simulation validation (e.g. comparison of experimental and simulated distributions), regression testing in the course of the software development process, and detector performance monitoring. Various sets of statistical tests have been added to the existing collection to deal with the one sample problem (i.e. the comparison of a data distribution to a function, including tests for normality, categorical analysis and the estimate of randomness). Improved algorithms and software design contribute to the robustness of the results. A simple user layer dealing with primitive data types facilitates the use of the toolkit both in standalone analyses and in large scale experiments.