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Spreadsheets in the Cloud - Not Ready Yet

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  • McCullough, Bruce D.
  • Yalta, A. Talha

Abstract

Cloud computing is a relatively new technology that facilitates collaborative creation and modification of documents over the internet in real time. Here we provide an introductory assessment of the available statistical functions in three leading cloud spreadsheets namely Google Spreadsheet, Microsoft Excel Web App, and Zoho Sheet. Our results show that the developers of cloud-based spreadsheets are not performing basic quality control, resulting in statistical computations that are misleading and erroneous. Moreover, the developers do not provide sufficient information regarding the software and the hardware, which can change at any time without notice. Indeed, rerunning the tests after several months we obtained different and sometimes worsened results.

Suggested Citation

  • McCullough, Bruce D. & Yalta, A. Talha, 2013. "Spreadsheets in the Cloud - Not Ready Yet," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i07).
  • Handle: RePEc:jss:jstsof:v:052:i07
    DOI: http://hdl.handle.net/10.18637/jss.v052.i07
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    References listed on IDEAS

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    1. A. Talha Yalta & A. Yasemin Yalta, 2009. "Wilkinson Tests and gretl," EHUCHAPS, in: Ignacio Díaz-Emparanza & Petr Mariel & María Victoria Esteban (ed.), Econometrics with gretl. Proceedings of the gretl Conference 2009, edition 1, chapter 16, pages 243-251, Universidad del País Vasco - Facultad de Ciencias Económicas y Empresariales.
    2. Yalta, A. Talha & Jenal, Olaf, 2009. "On the importance of verifying forecasting results," International Journal of Forecasting, Elsevier, vol. 25(1), pages 62-73.
    3. McCullough, B.D. & Heiser, David A., 2008. "On the accuracy of statistical procedures in Microsoft Excel 2007," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4570-4578, June.
    4. D. McCullough, B. & Wilson, Berry, 2002. "On the accuracy of statistical procedures in Microsoft Excel 2000 and Excel XP," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 713-721, October.
    5. Knusel, Leo, 2005. "On the accuracy of statistical distributions in Microsoft Excel 2003," Computational Statistics & Data Analysis, Elsevier, vol. 48(3), pages 445-449, March.
    6. Santosh Bangalore, Sai & Wang, Jelai & Allison, David B., 2009. "How accurate are the extremely small P-values used in genomic research: An evaluation of numerical libraries," Computational Statistics & Data Analysis, Elsevier, vol. 53(7), pages 2446-2452, May.
    7. McCullough, B. D. & Wilson, Berry, 1999. "On the accuracy of statistical procedures in Microsoft Excel 97," Computational Statistics & Data Analysis, Elsevier, vol. 31(1), pages 27-37, July.
    8. Sawitzki, Gunther, 1994. "Report on the Numerical Reliability of Data Analysis Systems," Computational Statistics & Data Analysis, Elsevier, vol. 18(2), pages 289-301, September.
    9. McCullough, B.D. & Wilson, Berry, 2005. "On the accuracy of statistical procedures in Microsoft Excel 2003," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 1244-1252, June.
    10. Knusel, Leo, 1998. "On the accuracy of statistical distributions in Microsoft Excel 97," Computational Statistics & Data Analysis, Elsevier, vol. 26(3), pages 375-377, January.
    11. Yalta, A. Talha, 2008. "The accuracy of statistical distributions in Microsoft® Excel 2007," Computational Statistics & Data Analysis, Elsevier, vol. 52(10), pages 4579-4586, June.
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    Cited by:

    1. Guy Mélard, 2014. "On the accuracy of statistical procedures in Microsoft Excel 2010," Computational Statistics, Springer, vol. 29(5), pages 1095-1128, October.

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