@article{olusegun2015programming,
  title = {Programming Development of Kolmogorov-Smirnov Goodness-of-Fit Testing of Data Normality as a Microsoft  Excel® Library Function},
  author = {Okeniyi Joshua Olusegun and Okeniyi and Elizabeth Toyin and Atayero Aderemi.A},
  year = 2015,
  url = {https://ibimapublishing.com/articles/JSSD/2015/238409/},
  journal = {Journal of Software and Systems Development},
  volume = (2015),
  pages = 15,
  doi = 10.5171/2015.238409,
  abstract = {This paper deliberates on the programming development of the Kolmogorov-Smirnov goodness-of-fit testing of data Normality as a library function in the Microsoft Excel® spreadsheet software, in which researchers normally store data for analysis and processing. The algorithmic program procedure utilised developed implementation of the Normality Kolmogorov-Smirnov D statistics for the one-sided and the two-sided test criteria as a library function in the Microsoft Excel® environment. For these programming developments, the Visual Basic for Applications® was employed for deploying macro embedment in the spreadsheet software. Successful programming development of the Normality K-S D statistics fosters implementation of the Normality K-S p-value estimation procedure also as a library function in the Microsoft Excel® environment. Test-applications of these programming developments in the study portray potency of accurate, speedy and economical procedure for testing compatibility of univariate data of real numbers to the Normal distribution, for datasets of n ≤ 2000 sample size.},
  keywords = {Normality testing; Kolmogorov-Smirnov statistics; machine precision arithmetic; Microsoft Excel® library function},
  note = Article ID: 238409
}