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      The uncertainty of the statistical data

      Preprint
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      ScienceOpen Preprints
      ScienceOpen
      Uncertainty, Statistic
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            Abstract

            ABSTRACT: Any result can be generated randomly and any random result is useless. Traditional methods define uncertainty as a measure of the dispersion around the true value and are based on the hypothesis that any divergence from uniformity is the result of a deterministic event. The problem with this approach is that even non-uniform distributions can be generated randomly and the probability of this event rises as the number of hypotheses tested increases. Consequently, there is a risk of considering a random and therefore non-repeatable hypothesis as deterministic. Indeed, it is believed that this way of acting is the cause of the high number of non-reproducible results. Therefore, we believe that the probability of obtaining an equal or better result randomly is the true uncertainty of the statistical data. Because it represents the probability that the data is useful and therefore the validity of any other analysis depends on this parameter.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            29 November 2021
            Affiliations
            [1 ] Independent
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PPNDDMU.v1
            e8f6dd24-f032-449e-b67f-a4d2596f333d

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            All data generated or analysed during this study are included in this published article (and its supplementary information files).
            Applied mathematics,Applications,Methodology
            Uncertainty,Statistic

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