A WEB-BASED SOFTWARE FOR THE CALCULATION OF THEORETICAL PROBABILITY DISTRIBUTIONS

Year 2021, Volume: 6 Issue: 1, 44 - 50, 29.06.2021

Fatma Hilal Yağın Emek Güldoğan Cemil Çolak

https://doi.org/10.52876/jcs.878742

Cited By: 2

Abstract

Abstract— Aim: The aim of this study is to develop a public web-based theoretical probability distributions software (KODY) that can calculate probabilities for discrete and continuous distributions.

Materials and Methods: The Discrete Uniform, Bernoulli, Binomial, Multinomial, Poisson, Geometric, Negative Binomial, Hypergeometric and Zeta (Zipf) distributions from the discrete distributions are explained. Among the continuous distributions, The Continuous Uniform, Beta, Normal, Log-Normal, Exponential, Gamma, Weibull, Rayleigh, Logistics, Pareto, Laplace, Cauchy and Erlang distributions are elucidated. Illustrative examples are presented on hypothetical medical data. The software was developed using the MATH and DASH libraries of the Python programming language.

Results: When making statistical analysis, the feature of the distribution is essential. Because the descriptive and analytical statistical methods to be applied to data with different distributions are also different. Probability distributions of variables are important in the effectiveness of these methods. For this reason, it is an essential step for researchers to determine the probability distributions of their data before starting their studies. It is thought that the software developed in this study will enable researchers to make the necessary calculations in probabilistic estimates regarding the theoretical probability distributions. The developed software can be accessed at http://biostatapps.inonu.edu.tr/KODY/.

Conclusion: The open access web-based software with Turkish/English language options may guide and contribute to researchers in probabilistic estimation processes regarding theoretical distributions. In the later stages of this study, it is foreseen to develop simulation processes based on each probability distribution.

Keywords— Discrete Probability Distributions, Continuous Probability Distributions, Web - Based Software, Python.

Keywords

Discrete Probability Distributions, Continuous Probability Distributions, Web - Based Software, Python

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