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Programming Development of Kolmogorov-Smirnov Goodness-of-Fit Testing of Data Normality as a Microsoft Excel® Library Function

机译:作为MicrosoftExcel®库功能的数据正态性的Kolmogorov-Smirnov拟合优度测试的编程开发

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摘要

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.
机译:本文研究了数据的Kolmogorov-Smirnov拟合优度测试的编程开发,该函数是MicrosoftExcel®电子表格软件中的一种库函数,研究人员通常在其中存储数据以进行分析和处理。该算法程序过程利用了针对单面和双面测试标准的Normality Kolmogorov-Smirnov D统计量的已开发实现,作为MicrosoftExcel®环境中的库函数。对于这些编程开发,使用Visual Basic forApplications®在电子表格软件中部署宏嵌入。 Normality K-S D统计信息的成功编程开发促进了Normality K-S p值估算程序的实现,该过程也作为MicrosoftExcel®环境中的库函数而实现。这些程序开发的测试应用程序在研究中表现出了准确,快速和经济的程序的功效,该程序对于n≤2000样本量的数据集,测试实数单变量数据与正态分布的兼容性。

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