Segue três artigos mostrando a razão do Excel ser inadequado pra análises estatísticas. Conforme os autores dos trabalhos:
No statistical procedure in Excel should be used until Microsoft documents that the procedure is correct; it is not safe to assume that Microsoft Excel’s statistical procedures give the correct answer. Persons who wish to conduct statistical analyses should use some other package.
Resumo:
The reliability of statistical procedures in Excel are assessed in three areas: estimation (both linear and nonlinear); random number generation; and statistical distributions (e.g., for calculating p-values). Excel's performance in all three areas is found to be inadequate. Persons desiring to conduct statistical analyses of data are advised not to use Excel.
On the accuracy of statistical procedures in Microsoft Excel 97 -B.D. Cullough,Berry Wilson- Computational Statistics & Data Analysis Elsevier 28 July 1999
Some of the problems that rendered Excel 97, Excel 2000 and Excel 2002 unfit for use as a statistical package have been fixed in Excel 2003, though some have not. Additionally, in fixing some errors, Microsoft introduced other errors. Excel's new and improved random number generator, at default, is supposed to produce uniform numbers on the interval (0,1); but it also produces negative numbers. Excel 2003 is an improvement over previous versions, but not enough has been done that its use for statistical purposes can be recommended.
On the accuracy of statistical procedures in Microsoft Excel 2003- B.D. McCullough,Berry WilsonComputational Statistics & Data Analysis Elsevier 15 June 2005
Resumo
Excel 2007, like its predecessors, fails a standard set of intermediate-level accuracy tests in three areas: statistical distributions, random number generation, and estimation. Additional errors in specific Excel procedures are discussed. Microsoft’s continuing inability to correctly fix errors is discussed. No statistical procedure in Excel should be used until Microsoft documents that the procedure is correct; it is not safe to assume that Microsoft Excel’s statistical procedures give the correct answer. Persons who wish to conduct statistical analyses should use some other package.
The reliability of statistical procedures in Excel are assessed in three areas: estimation (both linear and nonlinear); random number generation; and statistical distributions (e.g., for calculating p-values). Excel's performance in all three areas is found to be inadequate. Persons desiring to conduct statistical analyses of data are advised not to use Excel.
On the accuracy of statistical procedures in Microsoft Excel 97 -B.D. Cullough,Berry Wilson- Computational Statistics & Data Analysis Elsevier 28 July 1999
Resumo
Some of the problems that rendered Excel 97, Excel 2000 and Excel 2002 unfit for use as a statistical package have been fixed in Excel 2003, though some have not. Additionally, in fixing some errors, Microsoft introduced other errors. Excel's new and improved random number generator, at default, is supposed to produce uniform numbers on the interval (0,1); but it also produces negative numbers. Excel 2003 is an improvement over previous versions, but not enough has been done that its use for statistical purposes can be recommended.
Resumo
Excel 2007, like its predecessors, fails a standard set of intermediate-level accuracy tests in three areas: statistical distributions, random number generation, and estimation. Additional errors in specific Excel procedures are discussed. Microsoft’s continuing inability to correctly fix errors is discussed. No statistical procedure in Excel should be used until Microsoft documents that the procedure is correct; it is not safe to assume that Microsoft Excel’s statistical procedures give the correct answer. Persons who wish to conduct statistical analyses should use some other package.
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