2019•arXiv (Cornell University)Open access

Four Fundamental Questions in Probability Theory and Statistics

Paolo Rocchi

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Abstract

This study has the purpose of addressing four questions that lie at the base of the probability theory and statistics, and includes two main steps. As first, we conduct the textual analysis of the most significant works written by eminent probability theorists. The textual analysis turns out to be a rather innovative method of study in this domain, and shows how the sampled writers, no matter he is a frequentist or a subjectivist, share a similar approach. Each author argues on the multifold aspects of probability then he establishes the mathematical theory on the basis of his intellectual conclusions. It may be said that mathematics ranks second. Hilbert foresees an approach far different from that used by the sampled authors. He proposes to axiomatize the probability calculus notably to describe the probability concepts using purely mathematical criteria. In the second stage of the present research we address the four issues of the probability theory and statistics following the recommendations of Hilbert. Specifically, we use two theorems that prove how the frequentist and the subjectivist models are not incompatible as many believe. Probability has distinct meanings under different hypotheses, and in turn classical statistics and Bayesian statistics are available for adoption in different circumstances. Subsequently, these results are commented upon, followed by our conclusions

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This study has the purpose of addressing four questions that lie at the base of the probability theory and statistics, and includes two main steps. As first, we conduct the textual analysis of the most significant works written by eminent probability theorists. The textual analysis turns out to be a rather innovative method of study in this domain, and shows how the sampled writers, no matter he is a frequentist or a subjectivist, share a similar approach. Each author argues on the multifold aspects of probability then he establishes the mathematical theory on the basis of his intellectual conclusions. It may be said that mathematics ranks second. Hilbert foresees an approach far different from that used by the sampled authors. He proposes to axiomatize the probability calculus notably to describe the probability concepts using purely mathematical criteria. In the second stage of the present research we address the four issues of the probability theory and statistics following the recommendations of Hilbert. Specifically, we use two theorems that prove how the frequentist and the subjectivist models are not incompatible as many believe. Probability has distinct meanings under different hypotheses, and in turn classical statistics and Bayesian statistics are available for adoption in different circumstances. Subsequently, these results are commented upon, followed by our conclusions

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Available abstract

This study has the purpose of addressing four questions that lie at the base of the probability theory and statistics, and includes two main steps. As first, we conduct the textual analysis of the most significant works written by eminent probability theorists. The textual analysis turns out to be a rather innovative method of study in this domain, and shows how the sampled writers, no matter he is a frequentist or a subjectivist, share a similar approach. Each author argues on the multifold aspects of probability then he establishes the mathematical theory on the basis of his intellectual conclusions. It may be said that mathematics ranks second. Hilbert foresees an approach far different from that used by the sampled authors. He proposes to axiomatize the probability calculus notably to describe the probability concepts using purely mathematical criteria. In the second stage of the present research we address the four issues of the probability theory and statistics following the recommendations of Hilbert. Specifically, we use two theorems that prove how the frequentist and the subjectivist models are not incompatible as many believe. Probability has distinct meanings under different hypotheses, and in turn classical statistics and Bayesian statistics are available for adoption in different circumstances. Subsequently, these results are commented upon, followed by our conclusions

Key concepts: Frequentist inference, Subjectivism, Frequentist probability, Probability theory, Probability and statistics, Mathematical statistics, Applied probability, Bayesian statistics

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