On the Numerical Accuracy of Spreadsheets

Almiron, Marcelo G.; Lopes, Bruno; Oliveira, Alyson L. C.; Medeiros, Antonio C.; Frery, Alejandro C.

doi:10.18637/jss.v034.i04

Cited by 18 publications

(30 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As in other studies, c.f. reference [2], the first-lag sample autocorrelation is a challenging quantity to compute. None of the platforms here tested provided acceptable results.…”

Section: Discussionmentioning

confidence: 99%

How good are MatLab, Octave and Scilab for computational modelling?

Almeida¹,

Medeiros²,

Frery³

2012

Comput. Appl. Math.

View full text Add to dashboard Cite

Abstract. In this article we test the accuracy of three platforms used in computational modelling: MatLab, Octave and Scilab, running on i386 architecture and three operating systems (Windows, Ubuntu and Mac OS). We submitted them to numerical tests using standard data sets and using the functions provided by each platform. A Monte Carlo study was conducted in some of the datasets in order to verify the stability of the results with respect to small departures from the original input. We propose a set of operations which include the computation of matrix determinants and eigenvalues, whose results are known. We also used data provided by NIST (National Institute of Standards and Technology), a protocol which includes the computation of basic univariate statistics (mean, standard deviation and first-lag correlation), linear regression and extremes of probability distributions. The assessment was made comparing the results computed by the platforms with certified values, that is, known results, computing the number of correct significant digits.Mathematical subject classification: Primary: 06B10; Secondary: 06D05.

show abstract

“…As in other studies, c.f. reference [2], the first-lag sample autocorrelation is a challenging quantity to compute. None of the platforms here tested provided acceptable results.…”

Section: Discussionmentioning

confidence: 99%

How good are MatLab, Octave and Scilab for computational modelling?

Almeida¹,

Medeiros²,

Frery³

2012

Comput. Appl. Math.

View full text Add to dashboard Cite

show abstract

“…Recent contributions to the subject make up a whole section of Computational Statistics and Data Analysis published by McCullough (2008a), in particular Yalta (2008). See also Almiron et al (2010) and Hargreaves and McWilliams (2010), as well as a very complete web site held by Heiser (2009) (where the history of Microsoft "fixes" is nicely described). In those papers and that web site, the latest versions covered are Excel 2007 and Calc 3.0.…”

Section: Generalitiesmentioning

confidence: 99%

“…Meanwhile, Microsoft Office 2010 and OpenOffice 3.3 have been released, calling for an update of those studies. Note that Almiron et al (2010) also covers implementations over several operating systems (Microsoft Windows, Linux Ubuntu, Apple MacOS X) and several hardware platforms (Intel i386 and AMD amd64) and covers not only several releases of Excel and Calc but also an OpenOffice derivative for MacOS, NeoOffice, and GNU Oleo for Linux Ubuntu.…”

Section: Generalitiesmentioning

confidence: 99%

On the accuracy of statistical procedures in Microsoft Excel 2010

Mélard

2014

Comput Stat

124

View full text Add to dashboard Cite

All previous versions of Microsoft Excel until Excel 2007 have been criticized by statisticians for several reasons, including the accuracy of statistical functions, the properties of the random number generator, the quality of statistical add-ins, the weakness of the Solver for nonlinear regression, and the data graphical representation. Until recently Microsoft did not make an attempt to fix all the errors in Excel and was still marketing a product that contained known errors. We provide an update of these studies given the recent release of Excel 2010 and we have added OpenOffice.org Calc 3.3 and Gnumeric 1.10.16 to the analysis, for the purpose of comparison. The conclusion is that the stream of papers, mainly in Computational Statistics and Data Analysis, has started to pay off: Microsoft has partially improved the statistical aspects of Excel, essentially the statistical functions and the random number generator.

show abstract

“…They are available at http://www.itl.nist.gov/div898/strd/. The StRD has been widely used to assess the accuracy of statistical software and statistical functionality in spreadsheets; see, for example: McCullough (1998), McCullough (1999a), McCullough (1999b), Vinod (2000), Kitchen, Drachenberg, and Symanzik (2003), Nerlove (2005), Mineo and Richiusa (2005), Bustos and Frery (2006), Keeling and Pavur (2007), Yalta and Yalta (2007), Odeh, Featherstone, and Bergtold (2010), Almiron, Lopes, Oliveira, Medeiros, and Frery (2010), Keeling and Pavur (2011), Yalta (2012), Lomax (2013), and Melard (2014).…”

Section: Introductionmentioning

confidence: 99%

On the accuracy of linear regression routines in some data mining packages

McCullough

Mokfi

Almaeenejad

2018

WIREs Data Min & Knowl

View full text Add to dashboard Cite

While articles assessing the accuracy of traditional statistical packages are fairly commonplace, data mining software has escaped this important scrutiny. We apply the National Institute of Standards and Technology Statistical Reference Datasets tests for the numerical accuracy of statistical packages to 7 data mining packages: IBM Modeler, KNIME, Orange, Python, RapidMiner, Weka, and XLMiner. We find that one package has an unstable algorithm for the calculation of the sample variance and only two have reliable linear regression routines. Of these two packages that offer analysis of variance, one has a bad algorithm. The accuracy of statistical calculations in data mining packages cannot be taken for granted. This article is categorized under: Algorithmic Development > Statistics Application Areas > Data Mining Software Tools

show abstract

On the Numerical Accuracy of Spreadsheets

Cited by 18 publications

References 46 publications

How good are MatLab, Octave and Scilab for computational modelling?

How good are MatLab, Octave and Scilab for computational modelling?

On the accuracy of statistical procedures in Microsoft Excel 2010

On the accuracy of linear regression routines in some data mining packages

Contact Info

Product

Resources

About