THE PHILOSOPHY OF EXPLORATORY DATA-ANALYSIS
THE PHILOSOPHY OF EXPLORATORY DATA-ANALYSIS
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DOI：
10.1086/289110
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发表时间：
1983-01-01
影响因子：
1.7
通讯作者：
GOOD, IJ
中科院分区：
文献类型：
--
作者：
GOOD, IJ
本文试图对探索性数据分析（EDA）给出一个比以往更精确的定义，并为这一新兴的分支学科提供一个哲学基础。在描述性统计和EDA中，这些k元组或它们的函数以与人类和计算机能力相匹配的方式表示，以期找到非“kinkera”的模式。扭结是一种模式，它有一个可以忽略的概率，甚至部分潜在的解释。一个潜在的可解释的模式是一个可能存在一个足够的“解释性”的假设，这是另一个技术概率概念。即使我们找不到解释，也可以判断一个模式可能是潜在的可解释的。这里所理解的概率理论是一种偏序（区间值）、主观（个人）概率。其他与EDA哲学相关的主题包括数据的“还原”、弗朗西斯·培根的科学哲学、假设的自动表述、假设的连续深化、神经生理学和第二类理性。
This paper attempts to define Exploratory Data Analysis (EDA) more precisely than usual, and to produce the beginnings of a philosophy of this topical and somewhat novel branch of statistics.A data set is, roughly speaking, a collection of k-tuples for some k. In both descriptive statistics and in EDA, these k-tuples, or functions of them, are represented in a manner matched to human and computer abilities with a view to finding patterns that are not “kinkera”. A kinkus is a pattern that has a negligible probability of being even partly potentially explicable. A potentially explicable pattern is one for which there probably exists a hypothesis of adequate “explicativity”, which is another technical probabilistic concept. A pattern can be judged to be probably potentially explicable even if we cannot find an explanation. The theory of probability understood here is one of partially ordered (interval-valued), subjective (personal) probabilities. Among other topics relevant to a philosophy of EDA are the “reduction” of data; Francis Bacon's philosophy of science; the automatic formulation of hypotheses; successive deepening of hypotheses; neurophysiology; and rationality of type II.