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R versus Other Statistical Software

Author

Listed:
  • Dobre Ana Maria

    (National Institute of Statistics Bucharest, Romania)

  • Caragea Nicoleta

    (National Institute of Statistics, Romania Ecological University of Bucharest, Faculty of Economics Bucharest, Romania)

  • Alexandru Ciprian Antoniade

    (Ecological University of Bucharest, Faculty of Economics Bucharest, Romania)

Abstract

In this paper we intend to present an overview of the advantages of using R – the most powerful statistical software. The statements on R are exposed versus SAS and SPSS – actually the most used statistical software in Romania. The study also focuses on comparing strengths and weaknesses of SAS, SPSS and R. As an example on how R is much more flexible that the other software, we used a statistical analysis. We will see how dominant R is already in the academia and how is predicted to be in the commercial. It is time now for opensource powerful software for official statistics as well as for companies and business.

Suggested Citation

  • Dobre Ana Maria & Caragea Nicoleta & Alexandru Ciprian Antoniade, 2013. "R versus Other Statistical Software," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 484-488, May.
    • Handle: RePEc:ovi:oviste:v:xii:y:2012:i:1:p:484-488
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    Citations

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    Cited by:

    1. Ana Maria DOBRE & Nicoleta CARAGEA, 2015. "Producing small area estimation using R in the Romanian official statistics," Romanian Journal of Economics, Institute of National Economy, vol. 40(1(49)), pages 115-125, june.
    2. Diana Ioana POPA, 2016. "Influence Factors of the Economic Development Level Across European Countries," Romanian Statistical Review, Romanian Statistical Review, vol. 64(2), pages 3-16, June.

    More about this item

    Keywords

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    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

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