{"title":"The Philosophy of Probability Value Behavior: Fractions and Composite Probability Functions in the Continuous Case","authors":"A. Jughaiman","doi":"10.19044/esj.2024.v20n9p1","DOIUrl":null,"url":null,"abstract":"This paper focuses on probability value behavior in the case of continuous sample space by employing fractions intervals and composite functions. The study evaluates value behavior rather than finding values directly, which involves utilization of some concepts from continuity, geometric probability, and measure theory. This paper primarily uses an experiment that contains two major events, head H and tail T, in all their occurrence phases. This spread in infinite and uncountable fractions by a continuous motion within intervals and in the predominant circumstances where events are probabilistic values. As a result, every circumstance reflects many important characteristics of probability theory. Among the main results, this paper provides proven propositions that help design experiments upon understanding the case nature, with some explanations to the existing relation between probability value and the case nature. Also, this paper provides a proven corollary that allows visualizing negative probability values as a particular trial. This in turn proposes necessary uses for the composite probability function P_j 〖(p〗_i). Moreover, this paper provides numerical explanations of limits, which can demonstrate the nature of P_j 〖(p〗_i), alongside some techniques. Also, this paper considered conditional probability through some corollaries and the possibility of using the non-negative function of the interval i, alongside many important results in form of discussions.","PeriodicalId":12225,"journal":{"name":"European Scientific Journal, ESJ","volume":"41 36","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Scientific Journal, ESJ","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.19044/esj.2024.v20n9p1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper focuses on probability value behavior in the case of continuous sample space by employing fractions intervals and composite functions. The study evaluates value behavior rather than finding values directly, which involves utilization of some concepts from continuity, geometric probability, and measure theory. This paper primarily uses an experiment that contains two major events, head H and tail T, in all their occurrence phases. This spread in infinite and uncountable fractions by a continuous motion within intervals and in the predominant circumstances where events are probabilistic values. As a result, every circumstance reflects many important characteristics of probability theory. Among the main results, this paper provides proven propositions that help design experiments upon understanding the case nature, with some explanations to the existing relation between probability value and the case nature. Also, this paper provides a proven corollary that allows visualizing negative probability values as a particular trial. This in turn proposes necessary uses for the composite probability function P_j 〖(p〗_i). Moreover, this paper provides numerical explanations of limits, which can demonstrate the nature of P_j 〖(p〗_i), alongside some techniques. Also, this paper considered conditional probability through some corollaries and the possibility of using the non-negative function of the interval i, alongside many important results in form of discussions.
本文通过使用分数区间和复合函数,重点研究连续样本空间中的概率值行为。该研究评估的是值行为,而不是直接求值,这涉及到对连续性、几何概率和度量理论中一些概念的利用。本文主要使用一个包含两个主要事件(头部 H 和尾部 T)所有发生阶段的实验。在事件为概率值的主要情况下,通过区间内的连续运动,以无限和不可计数的分数扩散。因此,每种情况都反映了概率论的许多重要特征。在主要成果中,本文提供了一些经过验证的命题,有助于在理解情况性质的基础上设计实验,并对概率值与情况性质之间的现有关系做出了一些解释。此外,本文还提供了一个经过验证的推论,可将负概率值可视化为一个特定的试验。这反过来又为复合概率函数 P_j 〖(p〗_i)提出了必要的用途。此外,本文还提供了对极限的数值解释,可以证明 P_j 〖(p〗_i)的性质,同时还提供了一些技巧。此外,本文还通过一些推论和使用区间 i 的非负函数的可能性来考虑条件概率,并以讨论的形式给出了许多重要结果。