Vol.10, No.4, November 2021.                                                                                                                                                                           ISSN: 2217-8309

                                                                                                                                                                                                                          eISSN: 2217-8333


TEM Journal



Association for Information Communication Technology Education and Science

Chi-square of Pseudorandom Number Generator of Normal Distribution in C++17


Pavel Tomášek, Hana Tomášková, Jakub Rak


© 2021 Pavel Tomášek, published by UIKTEN. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. (CC BY-NC-ND 4.0)


Citation Information: TEM Journal. Volume 10, Issue 4, Pages 1495-1499, ISSN 2217-8309, DOI: 10.18421/TEM104-01, November 2021.


Received: 23 July 2021.

Revised:  15 September 2021.
Accepted: 22 September 2021.
Published: 26 November2021.




High quality pseudorandom number generators were needed in many software solutions throughout the history of programming. Nowadays, these generators play an even more significant role in software development. Generally, these generators bring a certain level of coincidence in some algorithms which need it. This work focuses on the statistical evaluation of one of the representatives of the generators using Pearson's Chi-square goodness of fit test. The generator of pseudorandom numbers under test is the specific implementation in the modern standard of the programming language of C++ (the standard of C++17). Results presented in this paper inform whether the numbers generated by the selected generator follow the desired probability distribution (normal).


Keywords –chi-square, pseudorandom number generator, C++, normal distribution.



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