著者
三中 信宏
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.38, no.2, pp.117-125, 2018-03-01 (Released:2018-05-18)
参考文献数
21

The recent controversy over the use and abuse of p-values in statistical data analysis sheds a light on the epistemological diversity of scientific researches and the nature of science. Since the nineteenth century theoretical statisticians including Karl Pearson, Ronald A. Fisher, Jerzy Neyman, and Egon S.Pearson constructed the mathematical basis of modern statistics, for example, experimental design, sampling distributions, or hypothesis testing, etc. However, statistical reasoning as empirical inference is not necessarily limited to the Neyman-Pearson’s decision-making paradigm. Any kind of non-deductive inference—for example, abduction—also uses statistics as an exploratory tool for relative ranking among alternative hypotheses and models. We must understand not only the proper use of statistical methods and procedures but also the nature of each science to which statistics is applied.
著者
三中 信宏
出版者
心理学評論刊行会
雑誌
心理学評論 (ISSN:03861058)
巻号頁・発行日
vol.59, no.1, pp.123-128, 2016 (Released:2018-04-13)
参考文献数
27
被引用文献数
3

The recent controversy over statistical data analyses sheds a light on a number of cases of abuse of statistical procedures. In this essay some practical aspects of statistical analyses, mainly in agricultural research, are discussed. During the past century eminent researchers, including K. Pearson, R. A. Fisher, J. Neyman, and E. S. Pearson, have established the theoretical basis of modern mathematical statistics, e.g., experimental design, sampling distributions, and hypothesis testing. Some users in psychology, agronomy, etc. might be liable to commit misconduct in statistical analysis. Of course while they are responsible for what they have done, they must understand not only the proper use of statistical methodology but also the characteristic of each science.
著者
三中 信宏
出版者
一般社団法人 日本応用数理学会
雑誌
応用数理 (ISSN:24321982)
巻号頁・発行日
vol.32, no.2, pp.80-86, 2022-06-24 (Released:2022-09-30)
参考文献数
34

In the field of statistical data analysis in research, there is considerable discussion about the details of statistical methods and statistical modeling applied to the actual data. However, the fact that philosophical and conceptual issues in statistical science lie behind a variety of practical problems is not often discussed in the open. Meanwhile, this paper discusses the relative comparison of competing hypotheses, model selection by AIC (Akaike’s Information Criterion), and the nature of statistics as “abduction” as nondeductive reasoning, which is based on the statistical criterion of “simplicity.”
著者
三中 信宏
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.28, no.Special_Issue_1, pp.S25-S34, 2007-10-01 (Released:2011-09-25)
参考文献数
37

Contemporary evolutionary biology has used various statistical methods for collecting and analyzing data. Here methods for estimating phylogenetic trees are reviewed in the context of recent history of evolutionary biology, especially of systematics and phylogenetics. Estimating evolutionary history based on character data (molecular or morphological) poses a couple of epistemological problems all of which are common to historical sciences in general. Karl Popper's philosophy of science, in particular, his theory of falsification and corroboration has been espoused by many theoretical phylogeneticists. In this paper the long-standing controversy on philosophical aspects of phylogenetics and its implications for statistical methods in this discipline is discussed.
著者
三中 信宏 岩田 洋佳 伊達 康博 曹 巍 Harshana Habaragamuwa 桂樹 哲雄 小林 暁雄 山中 武彦 櫻井 玄
出版者
日本計量生物学会
雑誌
計量生物学 (ISSN:09184430)
巻号頁・発行日
vol.44, no.1, pp.55-82, 2023-10-31 (Released:2023-12-06)
参考文献数
100

This review provides a comprehensive introduction to recent developments in agricultural statistics. Agricultural statistics, which began with Fisher’s design of experiments, has developed in various directions as the nature of the data it handles has changed. The ability to rapidly measure omics data, including DNA sequences, has led to methods such as genomic selection. It has become possible to comprehensively measure even the metabolites of living organisms, giving birth to a new field called metabolomics. The development of machine learning, including deep learning, has enabled the use of image data, which has been difficult to connect with agriculture and is creating new areas such as disease diagnosis of crops. In this review, we first refer to the statistics of Fisher’s era, recall the philosophy of science in statistics, and look at the prospects of modern agricultural statistics by taking a broad overview of new fields.
著者
三中 信宏
出版者
日本植物分類学会
雑誌
植物分類・地理 (ISSN:00016799)
巻号頁・発行日
vol.44, no.2, pp.151-184, 1993-12-30

歴史生物地理学におけるvicarianceの概念について, それがたどってきた概念史を概観した。もともと生物地理学で用いられてきたvicarianceは近縁種の空間的な「代置」(substitution)という分布パターンを意味しており, Hennig理論に基づく系統生物地理学はこの用法に準拠していた。一方, Croizatに始まる汎生物地理学もまた代置の意味でこの言葉を用いているが, 「代置的生物進化」(vicariant form-making)という進化理論を背景にしている点に特徴がある。これらの用法に対し, 分断生物地理学では同所的に分布する複数の生物群に対する共通原因すなわち生物相の「分断」(fragmentation)の意味でvicarianceを用いた。共通原因/個別原因としての分断/分散は, 分岐分析における共有派生形質/ホモプラシーに相当する関係にある。次に, 分断生物地理学が解こうとしている地域間の近縁性の問題を「居住地/居住者問題」(the "habitation-inhabitant"problem)として一般化した。居住者の系統関係と地理的分布の情報に基づいて居住地の系統関係を推定するというこの居住地/居住者問題は, 生物地理学だけでなく分子系統学・共進化解析などとも共通する問題である。これらの問題の共通点は, 「形質」それ自身が「系統」を持つという点である。最後に, 分断生物地理学の観点からこの居住地/居住者問題を解決するためのいくつかの解析的手法-成分分析法・ブルックス最節約法・群整合性分析法・三対象分析法-について議論した。種分岐図における欠損地域・広域分布種・重複出現がこれまで分断生物地理学において論議の的となってきた一つの理由は, それらを含む分岐図が通常の分岐分析で生じる分岐図の性質を満足していないことにある。半順序理論などの離散数学を用いることによりこれらの問題にアプローチできるだろう。