In this paper, I examine William Whewell’s (1794–1866) ‘Discoverer’s Induction’, and argue that it 21 supplies a strikingly accurate characterization of the logic behind many statistical methods, exploratory 22 data analysis (EDA) in particular. Such methods are additionally well-suited as a point of evaluation of 23 Whewell’s philosophy since the central techniques of EDA were not invented until after Whewell’s death, 24 and so couldn’t have influenced his views. The fact that the quantitative details of some very general 25 (...) methods designed to suggest hypotheses would so closely resemble Whewell’s views of how theories 26 are formed is, I suggest, a strongly positive comment on these views. (shrink)

For those who teach students in psychology, education, and the social sciences, the _Handbook of Demonstrations and Activities in the Teaching of Psychology, Second Edition_ provides practical applications and rich sources of ideas. Revised to include a wealth of new material, these invaluable reference books contain the collective experience of teachers who have successfully dealt with students' difficulty in mastering important concepts about human behavior. Each volume features a table that lists the articles and identifies the primary and secondary courses (...) in which readers can use each demonstration. Additionally, the subject index facilitates retrieval of articles according to topical headings, and the appendix notes the source as it originally appeared in _Teaching of Psychology_, the official journal of the Society for the Teaching of Psychology, Division Two of the American Psychological Association. Volume I consists of 97 articles about strategies for teaching introductory psychology, statistics, research methods, and the history of psychology classes. Divided into four sections, the book suggests ways to stimulate interest, promote participation, grasp psychological terminology, and master necessary scientific skills. (shrink)

William Petty's work has usually been regarded as an epistemic break in the history of statistical and politico-economic thought. In this paper, I argue that Petty's statistical notions stemmed from the natural-historical techniques he originally implemented to manage the Down Survey. Following Bacon, who viewed the description of trades as a paramount branch of natural history, Petty approached the art of surveying itself as an object of natural-historical analysis. He partitioned the surveying work into individual tasks (...) and implemented a meticulous division of labour, employing hundreds of disbanded soldiers as surveyors and using questionnaires to calibrate the responses of his ‘instruments’, as he called his specialized workers. By borrowing these methods from natural history to organize surveying work, Petty was able to conceptualize Ireland as a political body defined by tables of aggregate data. I then compare the Down Survey with John Graunt's observations on the bills of mortality to show that both are representative of a particular style of natural history, aimed at describing the natural and political state of a circumscribed territory. I close by considering other manifestations of ‘territorial natural history’, indicating a continuity between this research tradition and the appearance of statistics in the British Isles. (shrink)

During the twentieth century statistical methods have transformed research in the experimental and social sciences. Qualitative evidence has largely been replaced by quantitative results and the tools of statistical inference have helped foster a new ideal of objectivity in scientific knowledge. The paper will investigate this transformation by considering the genesis of analysis of variance and experimental design, statistical methods nowadays taught in every elementary course of statistics for the experimental and social sciences. These methods were developed (...) by the mathematician and geneticist R. A. Fisher during the 1920s, while he was working at Rothamsted Experimental Station, where agricultural research was in turn reshaped by Fisher’s methods. Analysis of variance and experimental design required new practices and instruments in field and laboratory research, and imposed a redistribution of expertise among statisticians, experimental scientists and the farm staff. On the other hand the use of statistical methods in agricultural science called for a systematization of information management and made computing an activity integral to the experimental research done at Rothamsted, permanently integrating the statisticians’ tools and expertise into the station research programme. Fisher’s statistical methods did not remain confined within agricultural research and by the end of the 1950s they had come to stay in psychology, sociology, education, chemistry, medicine, engineering, economics, quality control, just to mention a few of the disciplines which adopted them. (shrink)

In the last years, the surprising bosonic behavior that a many-fermion system may acquire has raised interest because of theoretical and practical reasons. This trans-statistical behavior is usually considered to be the result of approximation modeling methods generally employed by physicists when faced with complexity. In this paper, we take a tensor product structure and an ontology of properties approach and provide two versions of a toy model in order to argue that trans-statistical behavior allows for a realistic (...) interpretation. (shrink)

We owe most scientific knowledge to methods of inquiry that are never formally analyzed. The analysis of behavior does not call for hypothetico-deductive methods. Statistics, taught in lieu of scientific method, is incompatible with major features of much laboratory research. Squeezing significance out of ambiguous data discourages the more promising step of scrapping the experiment and starting again. As a consequence, psychologists have taken flight from the laboratory. They have fled to Real People and the human interest of “real life,” (...) to Mathematical Models and the elegance of symbolic treatments, to the Inner Man and the explanatory preoccupation with inferred internal mechanisms, and to Laymanship and its appeal to “common sense.” An experimental analysis provides an alternative to these divertissements.The “theories” to which objection is raised here are not the basic assumptions essential to any scientific activity or statements that are not yet facts, but rather explanations which appeal to events taking place somewhere else, at some other level of observation, described in different terms, and measured, if at all, in different dimensions. Three types of learning theories satisfy this definition: physiological theories attempting to reduce behavior to events in the nervous system; mentalistic theories appealing to inferred inner events; and theories of the Conceptual Nervous System offered as explanatory models of behavior. It would be foolhardy to deny the achievements of such theories in the history of science. The question of whether they are necessary, however, has other implications.Experimental material in three areas illustrates the function of theory more concretely. Alternatives to behavior ratios, excitatory potentials, and so on demonstrate the utility of rate or probability of response as the basic datum in learning. Functional relations between behavior and environmental variables provide an account of why learning occurs. Activities such as preferring, choosing, discriminating, and matching can be dealt with solely in terms of behavior, without referring to processes in another dimensional system. The experiments are not offered as demonstrating that theories are not necessary but to suggest an alternative. Theory is possible in another sense. Beyond the collection of uniform relationships lies the need for a formal representation of the data reduced to a minimal number of terms. A theoretical construction may yield greater generality than any assemblage of facts; such a construction will not refer to another dimensional system. (shrink)

Over the years, mathematics and statistics have become increasingly important in the social sciences1 . A look at history quickly confirms this claim. At the beginning of the 20th century most theories in the social sciences were formulated in qualitative terms while quantitative methods did not play a substantial role in their formulation and establishment. Moreover, many practitioners considered mathematical methods to be inappropriate and simply unsuited to foster our understanding of the social domain. Notably, the famous Methodenstreit also (...) concerned the role of mathematics in the social sciences. Here, mathematics was considered to be the method of the natural sciences from which the social sciences had to be separated during the period of maturation of these disciplines. All this changed by the end of the century. By then, mathematical, and especially statistical, methods were standardly used, and their value in the social sciences became relatively uncontested. The use of mathematical and statistical methods is now ubiquitous: Almost all social sciences rely on statistical methods to analyze data and form hypotheses, and almost all of them use (to a greater or lesser extent) a range of mathematical methods to help us understand the social world. Additional indication for the increasing importance of mathematical and statistical methods in the social sciences is the formation of new subdisciplines, and the establishment of specialized journals and societies. Indeed, subdisciplines such as Mathematical Psychology and Mathematical Sociology emerged, and corresponding journals such as The Journal of Mathematical Psychology (since 1964), The Journal of Mathematical Sociology (since 1976), Mathematical Social Sciences (since 1980) as well as the online journals Journal of Artificial Societies and Social Simulation (since 1998) and Mathematical Anthropology and Cultural Theory (since 2000) were established. What is more, societies such as the Society for Mathematical Psychology (since 1976) and the Mathematical Sociology Section of the American Sociological Association (since 1996) were founded. Similar developments can be observed in other countries. The mathematization of economics set in somewhat earlier (Vazquez 1995; Weintraub 2002). However, the use of mathematical methods in economics started booming only in the second half of the last century (Debreu 1991). Contemporary economics is dominated by the mathematical approach, although a certain style of doing economics became more and more under attack in the last decade or so. Recent developments in behavioral economics and experimental economics can also be understood as a reaction against the dominance (and limitations) of an overly mathematical approach to economics. There are similar debates in other social sciences. It is, however, important to stress that problems of one method (such as axiomatization or the use of set theory) can hardly be taken as a sign of bankruptcy of mathematical methods in the social sciences tout court. This chapter surveys mathematical and statistical methods used in the social sciences and discusses some of the philosophical questions they raise. It is divided into two parts. Sections 1 and 2 are devoted to mathematical methods, and Sections 3 to 7 to statistical methods. As several other chapters in this handbook provide detailed accounts of various mathematical methods, our remarks about the latter will be rather short and general. Statistical methods, on the other hand, will be discussed in-depth. (shrink)

This paper is concerned with the role of rational belief change theory in the philosophical understanding of experimental error. Today, philosophers seek insight about error in the investigation of specific experiments, rather than in general theories. Nevertheless, rational belief change theory adds to our understanding of just such cases: R. A. Fisher’s criticism of Mendel’s experiments being a case in point. After an historical introduction, the main part of this paper investigates Fisher’s paper from the point of view of rational (...) belief change theory: what changes of belief about Mendel’s experiment does Fisher go through and with what justification. It leads to surprising insights about what Fisher had done right and wrong, and, more generally, about the limits of statistical methods in detecting error. (shrink)

Characterizing the genetic structure of populations is of importance to evolutionary biology, to human disease gene mapping, and to forensic science. Sewall Wright introduced a set of F-statistics to describe population structure in 1951, and he emphasized that these quantities were ratios of variances. Responding to uncertainty over the best way to estimate F-statistics, Weir and Cockerham published a method-of-moments set of estimators in 1984. This paper continues to be widely cited, with over 7,000 citations to date. Some background to (...) the publishing history of the Weir and Cockerham paper is given here, along with subsequent developments and a discussion of current uses of Wright's F-statistics. (shrink)

A. W. F. Edwards is one of the most influential mathematical geneticists in the history of the discipline. One of the last students of R. A. Fisher, Edwards pioneered the statistical analysis of phylogeny in collaboration with L. L. Cavalli-Sforza, and helped establish Fisher's concept of likelihood as a standard of statistical and scientific inference. In this book, edited by philosopher of science Rasmus Grønfeldt Winther, Edwards's key papers are assembled alongside commentaries by leading scientists, discussing Edwards's (...) influence on their own research and on thinking in their field overall. In an extensive interview with Winther, Edwards offers his thoughts on his contributions, their legacy, and the context in which they emerged. This book is a resource both for anyone interested in the history and philosophy of genetics, statistics, and science, and for scientists seeking to develop new algorithmic and statistical methods for understanding the genetic relationships between and among species both extant and extinct. (shrink)

The Nature and Method of Economic Sciences: Evidence, Causality, and Ends argues that economic phenomena can be examined from five analytical levels: namely, a statistical descriptive approach, a causal explanatory approach, a teleological explicative approach, a normative approach and, finally, the level of application. The above viewpoints are undertaken by different but related economic sciences, including statistics and economic history, positive economics, normative economics, and the 'art of political economy'. Typically, positive economics has analysed economic phenomena using the (...) second approach, causally explaining and often trying to predict the future evolution of the economy. It has not been concerned with the ends selected by the individual or society, taking them as given. However, various new economic currents have emerged during the last 40 years, and some of these do assign a fundamental role to ends within economics. This book argues that the field of positive economics should adapt to deal with the issues that arise from this. The text attempts to discern the nature of economic phenomena, introducing the different approaches and corresponding economic sciences. It goes on to analyse the epistemological characteristics of these in the subsequent chapters, as well as their disciplinary inter-relations. This book is a valuable resource for students and scholars of the social sciences, philosophy, and the philosophy of economics. It will also be of interest to those researching political economy, and the development of economic thought. (shrink)

Automated facial recognition methods have become widely used as a way to ascertain the identity of individuals. Yet the methods by which facial recognition technologies (FRT) operate – the machinic performance of the perception of the human face – are often invisible to those under their gaze. This article investigates the machinic perception of the face through an FRT method known as eigenface, in order to both reveal and problematize the ways of seeing that underlie it. As part of its (...) algorithmic processes, eigenface produces an image. This image can be understood as a portrait of machine recognition, making visible the processes through which the algorithm performs recognition and ‘sees’ the human face. The eigenface portrait reveals a way of seeing that is based on statistical processes of pattern recognition. An analogue antecedent of this application of statistics to the recognition of facial images can be found in the composite portrait. Through a dialectical discussion of composite portraiture in multiple disciplinary fields ranging from sociology to philosophy and the visual arts, this article experiments with providing a cultural and social translation of machine processes of visual perception. The discussion shifts the focus of enquiry towards the aesthetics of the algorithmic process in order to provide an entry point for critique and a possible reimagination on algorithmic knowledge production. (shrink)

The fossil record is paleontology’s great resource, telling us virtually everything we know about the past history of life. This record, which has been accumulating since the beginning of paleontology as a professional discipline in the early nineteenth century, is a collection of objects. The fossil record exists literally, in the specimen drawers where fossils are kept, and figuratively, in the illustrations and records of fossils compiled in paleontological atlases and compendia. However, as has become increasingly clear since the (...) later twentieth century, the fossil record is also a record of data. Paleontologists now routinely abstract information from the physical fossil record to construct databases that serve as the basis for quantitative analysis of patterns in the history of life. What is the significance of this distinction? While it is often assumed that the orientation towards treating the fossil record as a record of data is an innovation of the computer age, it turns out that nineteenth century paleontology was substantially “data driven.” This paper traces the evolution of data practices and analyses in paleontology, primarily through examination of the compendia in which the fossil record has been recorded over the past 200 years. I argue that the transition towards conceptualizing the fossil record as a record of data began long before the emergence of the technologies associated with modern databases (such as digital computers and modern statistical methods). I will also argue that this history reveals how new forms of visual representation were associated with the transition from seeing the fossil record as a record of objects to one of data or information, which allowed paleontologists to make new visual arguments about their data. While these practices and techniques have become increasingly sophisticated in recent decades, I will show that their basic methodology was in place over a century ago, and that, in a sense, paleontology has always been a “data driven” science. (shrink)

Work throughout the history and philosophy of biology frequently employs ‘chance’, ‘unpredictability’, ‘probability’, and many similar terms. One common way of understanding how these concepts were introduced in evolution focuses on two central issues: the first use of statistical methods in evolution (Galton), and the first use of the concept of “objective chance” in evolution (Wright). I argue that while this approach has merit, it fails to fully capture interesting philosophical reflections on the role of chance expounded by (...) two of Galton's students, Karl Pearson and W.F.R. Weldon. Considering a question more familiar from contemporary philosophy of biology—the relationship between our statistical theories of evolution and the processes in the world those theories describe—is, I claim, a more fruitful way to approach both these two historical actors and the broader development of chance in evolution. (shrink)

Surprise—operationalized as looking time—has a long history in developmental research, providing a window into the perception and cognition of infants. Recently, however, a number of developmental researchers have considered infants’ and children's surprise in its own right. This article reviews empirical evidence and computational models of complex statistical inferences underlying surprise, and discusses how these findings relate to the role that surprise appears to play as a catalyst for learning.

This book analyzes the origins of statistical thinking as well as its related philosophical questions, such as causality, determinism or chance. Bayesian and frequentist approaches are subjected to a historical, cognitive and epistemological analysis, making it possible to not only compare the two competing theories, but to also find a potential solution. The work pursues a naturalistic approach, proceeding from the existence of numerosity in natural environments to the existence of contemporary formulas and methodologies to heuristic pragmatism, a concept (...) introduced in the book's final section. This monograph will be of interest to philosophers and historians of science and students in related fields. Despite the mathematical nature of the topic, no statistical background is required, making the book a valuable read for anyone interested in the history of statistics and human cognition. (shrink)

An early example is von Neumann's and Charney's Princeton Meteorological Project in the period 1946–53 which ended with daily numerical prediction in less than 2 hours. After this stage, the questions of long-range forecasting and general circulation of the atmosphere became of greater importance. The late 1950s saw the emergence of an alternative: were atmospheric models used mainly for prediction or understanding? This controversial debate in particular occurred during an important colloquium in Tokyo in 1960 which gathered together J. Charney, (...) E. Lorenz, A. Eliassen, and B. Saltzman, among others, and witnessed discussions on statistical methods for predictions and/or maximum simplification of dynamic equations. This phase ended in 1963 with Lorenzs seminal paper on “Deterministic non periodic flows.”. (shrink)

The central theme of Japanese subnational governmental study has been centerlocal relations and the administrative institutions that define the relations. Indeed, one needs to ask what determines subnational policy outcomes, to what degree the national influence affects the determinants, and under what conditions these determinants function autonomously. The present paper directly examines the subnational policymaking process itself, not the center–local relations, and tries to understand its mechanism. The paper proposes a research framework using a statistical method that has been (...) developed in the area of diffusion study. In the framework, national influence is integrated into an analysis of subnational policymaking as one of the factors that affect policy determinants. Using the framework, the paper analyzes the process of four regional policies, which will lead to a better understanding of subnational policymaking. (shrink)

This article discusses the early history of academic statistics in the Netherlands in relation to the reform challenges of the Dutch state. Statistics, before it developed into a predominantly quantitative social science, was adopted around 1800 by Adriaan Kluit as a method for shaping and articulating his political vision. Kluit's politics, the article suggests, echoed the specific outlook on the ‘intrinsic power’ of the Dutch Republic as a trading state that was developed during William IV's stadholderate in the mid (...) eighteenth century. Through the ideas of later writers and statesmen who had trained as statisticians this same approach to envisaging the Dutch future in international trade and politics was carried over into nineteenth-century Dutch political economy and constitutional reform. (shrink)

Despite the promises made by molecular evolutionists since the early 1960s that phylogenies would be readily reconstructed using molecular data, the construction of molecular phylogenies has both retained many methodological problems of the past and brought up new ones of considerable epistemic relevance. The field is driven not only by changes in knowledge about the processes of molecular evolution, but also by an ever-present methodological anxiety manifested in the constant search for an increased objectivity—or in its converse, the avoidance of (...) subjectivity.This paper offers an exhaustive account of the methodological and conceptual difficulties embedded in each of the steps required to elaborate molecular phytogenies. The authors adopt a historical perspective on the field in order to follow the development of practices that seek to increase the objectivity of their methods and representations. These include the adoption and development of explicit criteria for evaluation of evidence, and of procedures associated with methods of statistical inference, quantification and automation. All these are linked to an increasing use of computers in research since the mid 1960s. We will show that the practices of objectivity described are highly dependent on the problems and tools of molecular phylogenetics. (shrink)

This paper examines the subversive role of statistics paleontology at the end of the 19th and the beginning of the 20th centuries. In particular, I will focus on German paleontology and its relationship with statistics. I argue that in paleontology, the quantitative method was questioned and strongly limited by the first decade of the 20th century because, as its opponents noted, when the fossil record is treated statistically, it was found to generate results openly in conflict with the Darwinian theory (...) of evolution. Essentially, statistics questions the gradual mode of evolution and the role of natural selection. The main objections to statistics were addressed during the meetings at the Kaiserlich-Königliche Geologische Reichsanstalt in Vienna in the 1880s. After having introduced the statistical treatment of the fossil record, I will use the works of Charles Léo Lesquereux, Joachim Barrande, and Henry Shaler Williams to compare the objections raised in Vienna with how the statistical treatment of the data worked in practice. Furthermore, I will discuss the criticisms of Melchior Neumayr, one of the leading German opponents of statistical paleontology, to show why, and to what extent, statistics were questioned in Vienna. The final part of this paper considers what paleontologists can derive from a statistical notion of data: the necessity of opening a discussion about the completeness and nature of the paleontological data. The Vienna discussion about which method paleontologists should follow offers an interesting case study in order to understand the epistemic tensions within paleontology surrounding Darwin’s theory as well as the variety of non-Darwinian alternatives that emerged from the statistical treatment of the fossil record at the end of the 19th century. (shrink)

The article examines the peculiarities of Christian personalism of Markellin Olesnitskyi, a professor at the Kyiv Theological Academy, the author of insightful works on Christian ethics, psychology, and pedagogy. There is an analysis of the conceptual approaches of the Kyiv scholar to the concept of the human individuality. Attention is drawn to those conceptual influences which contributed to the personalistic position of Olesnitskyi. They were G. Leibniz and F. Schleiermacher. In his studies, the Kyiv scholar always took into account the (...) ideas of these thinkers concerning a human and his or her individuality. In particular, he liked the idea of Leibniz, who considered a individuality as a “complete whole”, a certain singularity, the conceptual definition of which does not require the treatment of general entities. Also, he was inspired by the ideas of Schleiermacher, for whom individuality was a special modification of mankind. Schleiermacher thought that the human nature could not be considered separately from the individual selfexpression, cultural diversity of people. It was discovered that the Kyiv scholar needed the analysis of the human individuality for the research of the human personality that was considered as an individual having own personality. This makes it possible to consider the personality as a “being-for-itself”, as an independent being that is capable of making a moral choice. Olesnitskyi treats a person as a subjective focus of reason, will, and feelings, as well as the basis of history. In the article, one can see how the Kyiv professor treats attempts to implement mathematical and statistical methods to the study of social life. It is worth mentioning that those attempts were innovative for that period of time. The article includes an analysis of the standpoints of famous European researchers, among whom there were J. Süssmilch, A. Quetelet, H. Buckle, A. Wagner, and A. Oettingen. They demonstrated the efficiency of these methods application for both the analysis of the social and economic life of society and the study of his moral life, which made possible the appearance of social ethics. One can notice the positive as well as the critical attitude of the Kyiv acholar towards the already-mentioned research. (shrink)

To succeed, political science usually requires either prediction or contextual historical work. Both of these methods favor explanations that are narrow-scope, applying to only one or a few cases. Because of the difficulty of prediction, the main focus of political science should often be contextual historical work. These epistemological conclusions follow from the ubiquity of causal fragility, under-determination, and noise. They tell against several practices that are widespread in the discipline: wide-scope retrospective testing, such as much large-n statistical work; (...) lack of emphasis on prediction; and resources devoted to ‘pure theory’ divorced from frequent empirical application. I illustrate, via Donatella della Porta’s work on political violence, the important role that is still left for theory. I conclude by assessing the scope for political science to offer policy advice. (shrink)

In 1984 and 1985 Ralph Hall and I presented statistical methodologies, based on inductive statistics and the comparative method, to determine the rhythmical qualities of Latin prose from the third to early sixth century A.D. We continued our work with the publication of articles on the final clausulae in the legal codes and Augustine's letters and on rhythms in internal positions, while I produced studies of the clausulae in the Pseudo-Sallustiana and Ammianus.

To date, no satisfactory account of the connection between natural-scientific and historical explanation has been given, and philosophers seem to have largely given up on the problem. This paper is an attempt to resolve this old issue and to sort out and clarify some areas of historical explanation by developing and applying a method that will be called “pragmatic explication” involving the construction of definitions that are justified on pragmatic grounds. Explanations in general can be divided into “dynamic” and “static” (...) explanations, which are those that essentially require relations across time and those that do not, respectively. The problem of assimilating historical explanations concerns dynamic explanation, so a general analysis of dynamic explanation that captures both the structure of natural-scientific and historical explanation is offered. This is done in three stages: In the first stage, pragmatic explication is introduced and compared to other philosophical methods of explication. In the second stage pragmatic explication is used to tie together a series of definitions that are introduced in order to establish an account of explanation. This involves an investigation of the conditions that play the role in historiography that laws and statistical regularities play in the natural sciences. The essay argues that in the natural sciences, as well as in history, the model of explanation presented represents the aims and overarching structure of actual causal explanations offered in those disciplines. In the third stage the system arrived at in the preceding stage is filled in with conditions available to and relevant for historical inquiry. Further, the nature and treatment of causes in history and everyday life are explored and related to the system being proposed. This in turn makes room for a view connecting aspects of historical explanation and what we generally take to be causal relations. (shrink)

This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems — history-based generative parsing models. We report experimental results showing that memory-based learning outperforms many commonly used methods for this task (Witten-Bell, Jelinek-Mercer with fixed weights, decision trees, and log-linear models). However, we can connect these results with the commonly used general class of deleted interpolation models by showing that certain types of memory-based learning, including the (...) kind that performed so well in our experiments, are instances of this class. In addition, we illustrate the divergences between joint and conditional data likelihood and accuracy performance achieved by such models, suggesting that smoothing based on optimizing accuracy directError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMapError: Illegal entry in bfrange block in ToUnicode CMaply might greatly improve performance. (shrink)

The success of historical demography in establishing through statistical means the existence of family limitation in the past demonstrates that the methods of the quantitative social sciences can explain some problems better than traditional historiographical tools. In this case no literary evidence was available, and even if evidence existed it would have been too distorted to be reliable. Such findings may help historians understand broader issues such as the origins of the Industrial Revolution. Historical demography also may provide clues (...) about the revolutionary process in Western Europe. At the same time, the transition within demography itself from a "transversal" to a "longitudinal" style of analysis suggests that it is as important for the social scientist to become "historical" as it is for the historian to become "social-scientific.". (shrink)

Statistical procedures can be applied to episodes in the history of science in order to weight attributes to predict short-term survival of theories; an asymptotic method is used to show that short-term survival is a valid proxy for ultimate survival; and a theoretical argument is made that ultimate survival is a valid proxy for objective truth. While realists will appreciate this last step, instrumentalists do not need it to benefit from the actuarial procedures of cliometric metatheory. Introduction A (...) plausible proxy for Peircean consensus Assessing the validity of theory attributes as predictors of theory survival 3.1 Linear discriminant function 3.2 Factor analysis 3.3 Taxometric analysis Verisimilitude index Satisfying both instrumentalists and realists Recapitulation Implementation of cliometric metatheory * Correspondence about this article may be addressed to Leslie Yonce at pemeehle{at}umn.edu' + u + '@' + d + ''//--> This article had been completed by Paul Meehl at the time of his death on 14 February 2003. His wife, Leslie J. Yonce, is grateful to Keith Gunderson (University of Minnesota, Center for Philosophy of Science) and Niels G. Waller (Psychology Department, Vanderbilt University) for advice with some final editing details. (shrink)

Why was Hensen unsuccesful in the quantification of ecological sampling? No aspect of plankton research itself seems to have hindered quantification; both collecting methods and taxonomy were sufficiently advanced. The reason is probably that at the time he began sampling, Hensen had to devise his own statistical methods for expressing the reproducibility and validity of samples. Hensen might have succeeded in this if he had overcome prevalent nineteenth-century attitudes toward randomness.The statistical literature of medicine and physics with which (...) Hensen was probably familiar gave methods for expressing reproducibility and for comparing differences between means of different sets of observations. For example, a student of Poisson writing on medical statistics advocated using Poisson's limit (standard error 2√2) to test the difference between two means56. Other authors suggested that differences between means were most meaningful if very large numbers of observations were used.57 In his laboratory subsampling, Hensen used the propable error as a limit about means. In this and other ways, he seems most indebted to the physicist Ernst Abbe for statistical methods.58 However, all the methodology available to Hensen had been developed for situations in which errors are a property of the measurement or sampling process, and not of the phenomena themselves. The available methods for measuring reproducibility were based on the assumption that differences from the average were small and that they tended to accumulate about the mean in a bell-shaped pattern. Hensen constantly reinvestigated the distribution of plankton numbers about the average using a different method each time. Westergaard points out that medical statisticians did not make such investigations with their biological data.59To a considerable extent, biological sampling problems forced development of theory because samples afforded the only information on a pattern in water or soil which could not be directly observed. The sampling methods of Laplace and the late nineteenth-century government statisticians contrasted strongly with Hensen's because, either through subjective knowledge of the population sampled or through censuses, they attempted to choose representative or typical samples.60 The high reproducibility and validity of representative sampling is attained by knowing more about a population than a biologist can ordinarily know. The uncertain reproducibility and validity of biological sampling spurred the development of formal sampling theory.A formal sampling theory developed only after change in the general intellectual attitude toward randomness, which was reflected in nineteenth-century statistics.61 The ninteenth-century attitude that randomness is not part of nature changed in the twentieth century to a view of randomness as a property of nature.62 The physicist's incorporation of randomness into physical models in response to this intellectual change late in the nineteenth-century is discussed by Bork.63 In biology, the change was initiated by the attention Darwin focused on morphological variation. The English biometricians — Francis Galton and W. F. R. Weldon, for example — were prominent in developing methods for the analysis of biological variation.64 Most pertinent to the development of sampling theory was Karl Pearson's use of frequency distributions as models of biological variation. In ecology, quantification was brought about by Ronald Fisher more than by anyone else; he incorporated randomness into sampling plans and built upon the methods developed earlier for analysis of individual variation. Fisher's use of random sampling allowed comparison between the sample collections and the collections expected from a model population of known patterning (calculated with a frequency distribution). This is a much more efficient method of determining the validity of a sample than Hensen's comparison of collections with a model uniform collection. Intellectual background and accumulated biological information caused Fisher to find variability where Hensen had seen uniformity.In summary, Victor Hensen became interested in fisheries research because of the economic importance of fishing to Germany. Hensen had considerable understanding of the prerequisites for valid sampling, but the value of his quantitative approach was limited by the general preconceptions shared by most nineteenth-century biologists. Through Hensen's efforts many other biologists were stimulated to undertake quantitative samples, even though the statistical methods for analyzing variation among populations developed only after methods for analyzing variation among individuals had been developed. *** DIRECT SUPPORT *** A8402011 00003. (shrink)

In 1747, James Lind carried out an experiment which proved the usefulness of citrus fruit as a cure for scurvy. Nonetheless, he rejected the earlier hypothesis of Bachstrom that the absence of fresh fruit and vegetables was the only cause of the disease. I explain why it was rational for James Lind not to accept Bachstrom’s explanation. I argue that it was the urge for scientific understanding that guided Lind in his rejection and in the development of his alternative theory (...) that humidity was the primary cause of the disease. Central in this process was the search for causal mechanisms which could provide understanding of how the disease developed and which fitted in with the knowledge of the time. Given that the relevant background knowledge and statistical methods were not yet available to Lind, he was right to prefer his own explanation to that of Bachstrom. Although his explanation turned out to be wrong, and Bachstrom’s right, from a historical point of view it offered deeper causal understanding of both the development of the disease and the preventive and curative effects of fresh vegetable food. This case study illustrates how the search for causal mechanisms can not only be enlightening, but also very misleading. (shrink)

Eighteenth-century German Statistik was an empirical and descriptive discipline of "the land and the people." As the study of material conditions it provided governments with information to assess the strength of their own state in comparison with others. Its adherents' claim that Statistik was a useful science, however, was severely tempered by their empirical method and holistic view of society. As a "science of the present" it was seriously challenged by the recognition of the essential historicity of its subject matter. (...) Both circumstances explain the decline of Statistik from which mathematical statistics, political economy, and political historiography profited. (shrink)

Review of: A History of Sociological Research Methods in America, 1920-1960, by Jennifer Platt. -/- One might expect a history of research methods in sociology during the 40 years this book examines to deal with such questions as the conceptual preconditions for the statistical techniques employed during the period, the changes in statistical practice, the failure of the effort to measure attitudes in a dramatically more precise way, the failure of the many hopes and expectations of (...) methodologists, for the creation of a true science, and so forth. Some of these issues do peep out from the text now and then. But Platt's central concern is quite different. Despite the title, the book is not concerned with the development of techniques. It is instead a highly polemical attack on various previous writers and certain conventional historical opinions about this period. (shrink)

Catatonia is a psychomotor disorder that has gone through numerous descriptions since 1874, reflecting the many changes in psychiatric disease conceptualization that have occurred within that time frame. Catatonia has been variously described as a distinct disease entity, as a part of schizophrenia, and as a nonspecific manifestation of many disorders. Because of its association with schizophrenia, the description of catatonia was particularly affected by the psychopharmacological era, beginning in the 1950s, and by the development of the Diagnostic and (...) class='Hi'>Statistical Manual of Mental Disorders (DSM). Changing trends in psychiatric research—especially the brain-based disease model, research methods favoured by the evidence-based medicine movement, and the codes and categories of the DSM—also profoundly influenced the evolving concept of catatonia. This paper discusses these important factors that affected recognition, treatment, and study of catatonia in order to reveal the biases and assumptions made when constructing a disease concept. (shrink)

At the center of this work stands the anthropometric research program during World War I for studying constitutional medicine and the connected series of investigations by the medical internists Theodor Brugsch, Hermann Rautmann and Max Berliner, their advances in the statistics of variability as well as the subsequent debate in constitutional medicine and pathology on the definition of the physical norm.In order to create a data basis for the “normal” body in the study of constitutional medicine, a series of young (...) German internists undertook comprehensive anthropometric studies in the context of World War I, thereby taking advantage of the opportunity offered them by war to conduct a series of examinations of soldiers, but without having first reflected on methods of measurement, comparison, and evaluation. At the same time, the concept of the “normal” body, then only vaguely formed, still needed to be critically expounded. However, this changed during the subsequent period and led not only to a stronger emphasis on methodology, rather also to greater competency in mathematical statistics and philosophical cogitation on the meaning of the “norm”. In this way, constitutional medicine originated the potent medical norm debate of the early 1920s which still resonates in medical theory today. By this means the few years following the end of World War I not only represented a turning point for constitutional medicine regarding the reflective use of methodology, but also introduced a new orientation of their research questions: away from the “normal” body to individuality. (shrink)

1. Introduction : humanity's urge to understand -- 2. Elements of scientific thinking : skepticism, careful reasoning, and exhaustive evaluation are all vital. Science Is universal -- Maintaining a critical attitude. Reasonable skepticism -- Respect for the truth -- Reasoning. Deduction -- Induction -- Paradigm shifts -- Evaluating scientific hypotheses. Ockham's razor -- Quantitative evaluation -- Verification by others -- Statistics : correlation and causation -- Statistics : the indeterminacy of the small -- Careful definition -- Science at the frontier. (...) When good theories become ugly -- Stuff that just does not fit -- 3. Christopher Columbus and the discovery of the "Indies" : it can be disastrous to stubbornly refuse to recognize that you have falsified your own hypothesis -- 4. Antoine Lavoisier and Joseph Priestley both test the befuddling phlogiston theory : junking a confusing hypothesis may be necessary to clear the way for new and productive science -- 5. Michael Faraday discovers electromagnetic induction but fails to unify electromagnetism and gravitation : it is usually productive to simplify and consolidate your hypotheses -- 6. Wilhelm Röntgen intended to study cathode rays but ended up discovering X-rays : listen carefully when Mother Nature whispers in your ear : she may be leading you to a Nobel Prize -- 7. Max Planck, the first superhero of quantum theory, saves the universe from the ultraviolet catastrophe : assemble two flawed hypotheses about a key phenomenon into a model that fits experiment exactly and people will listen to you even if you must revolutionize physics -- 8. Albert Einstein attacks the problem "Are atoms real?" from every angle : solving a centuries-old riddle in seven different ways can finally resolve it -- 9. Niels Bohr models the hydrogen atom as a quantized system with compelling exactness, but his later career proves that collaboration and developing new talent can become more significant than the groundbreaking research of any individual -- 10. Conclusions, status of science, and lessons for our time. Conclusions from our biographies -- What thought processes lead to innovation? -- Is the scientist an outsider? -- The status of the modern scientific enterprise -- Lessons for our time -- Can the scientific method be applied to public policy? -- Why so little interest in science? -- Knowledge is never complete. (shrink)

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

The book deals with the changing nature and with the history of the concept of scientific determinism from the classical mechanics until the time immediately preceding quantum mechanics: such a historical-philosophical reconstruction is aimed at (1) signalizing and overcoming the deficiencies of the received opinion on the topic and (2) understanding better a concept which has influenced science from the beginning. -/- Before dealing with historical matters I develop in the first Chapter a kind of new, three-dimensional “measurement system” (...) for analyzing any concept of scientific determinism: many different concepts have been developed in the course of history, and we need a classification system which, on the one hand, is inclusive and broad enough to deal with different concepts; on the other hand, which makes possible to differentiate with some precision between them. My “measurement system” has three dimension or parameter: the “strength” (of the determining link between different states of the physical system), the “depth” (depending on how strong the ontological commitment of the particular concept of scientific determinism is), and the breadth (referring to the domain or the object, to which a deterministic evolution is ascribed). -/- In the second chapter I discuss briefly some main shortcomings of the received opinion about scientific determinism. Then I try to identify the “core” of scientific determinism at its origins while at the same time embedding it in the broader historical-cultural context especially of the Renaissance. On the one hand I show how the core of scientific determinism was mathematical, and this distinguished it from other related concepts, as mechanism, the principle of sufficient reason, and the aristotelic conception of science. On the other hand, precisely the support which these related concepts provided to scientific determinism, together with its mathematical nature, endowed it with an incredible resistance against empirical classification. -/- In the following three chapters I analyze the historic-philosophical development of scientific determinism along the three parameter of my measurement system. -/- In the third Chapter I reconstruct the weakening of scientific determinism with respect to its depth: the starting point is the question about the extent in which the deterministic mathematical descriptions do refer. In the development of mechanics into analytical mechanics the more and more formal character of its mathematical descriptions became evident and it became less obvious that these formal, deterministic structures also have an immediate material truth. Parallel developments within epistemology, starting with Kantian philosophy (which I deal with quite in detail), let the deterministic structures (principle, laws, equations, causal relations) appear less absolute and real and more as a product of reason, as conventions, or as models. A brief consideration of the interpretation of mechanics and its principles by Jacobi, Hertz, Mach and Poincaré shows the implications of these developments. -/- The fourth chapter reconstructs the weakening of scientific determinism with respect to the strength of the determining link: here my work deepens the track which has been opened by Ian Hacking, who interpreted the so-called “probabilistic revolution” in the 19th Century as the main reason for the erosion of determinism. The increasing pervasiveness of statistical methods in the social and natural sciences in the course of the 19th Century gave rise to a conception of scientific laws which could dispense with strict determinism. A new, empirical interpretation of probability (Frequentism) and the statistical explanation of thermodynamic phenomena in physics even suggested chance phenomena to be a necessary condition for the emergence of natural laws. -/- The last part of my work (Ch. 5, 6 and 7) considers the period (2nd half of the 19th century until ca. 1920) in which the concept of scientific determinism became explicit and was discussed as a world-picture or a world-view – that is, in its maximal breadth. I argue that there were two main reasons for the emergence of an explicit and ideological opposition “determinism vs. indeterminism” at that time: the first was the successful application of the deterministic paradigm to sociology, history, physiology and psychology in the course of the 19th Century, which provided scientific determinism with ethical implications (in particular with respect to the problem of free will, which scientific determinism seemed to deny). The second, related reason is that in the 19th Century natural scientists became public men, science was increasingly popularized and scientific issues were increasingly related to life-issues, to worldview-questions, and even to politics. In Chapter 6 I reconstruct the debates on the issue “determinism vs. indeterminism” in such a public, ideological and sometimes even political context. Among the discussants were Fechner, Du Bois-Reymond, Helmholtz, Bernard, Ostwald, Haeckel, Boussinesq, Maxwell, Boutroux, Poincaré, Renouvier, James und Peirce. Also in Vienna the debate on the issue of determinism was fervid and took ideological and political connotations: Michael Stöltzner and Deborah Coen have pointed to a particular tradition of “Vienna Indeterminism” (Stöltzner), or Viennese liberal probabilism (Coen), which was characterized by a strongly empirical conception of science and by the full acceptance and appreciation of statistical thinking in science. In the last Chapter of my work I focus on the early philosophy of Edgar Zilsel, a philosopher who stood near to the Vienna Circle and who has been much neglected in the literature by now, and I suggest considering it as part of the “Vienna Indeterminism”. First, I show how he gave an indeterministic foundation both to statistical and causal knowledge as well as to irreversibility in physics. Second, I inquire into his philosophy of probability and show how it developed in parallel to the ones of Hans Reichenbach and Richard von Mises. Finally, Zilsel happens to be a further, relevant case-study for pointing to the ideological and political side of the issue of determinism. -/- At the end of this reconstruction it should have become clear how no physical theory, no empirical evidence and no experimental confirmation can support or contradict scientific determinism in its non-trivial formulations. The validity of any such formulation depends strongly not only (from the systematical point of view) from the definition of other concepts (like time, physical state, causality etc.), but also from the particular conception of science which more or less implicitly constitutes its background, and which is subjected to historical change. -/- (ISBN: 9783495491034). (shrink)

A causal-comparative, mixed methods design was used to study a partnership between a university and school district formed with the goal of improving history teachers’ United States history content knowledge to raise student engagement and achievement. Data were collected from middle and high school history teachers including teacher interviews, classroom observations, and student work. Student engagement surveys and academic performance data were also collected. Student academic performance was positively impacted and changes in classroom practice were found in (...) the treatment group. However, differences in student engagement between groups were not found to be statistically significant. (shrink)

This paper examines Karl Alfred von Zittel’s practice in order to uncover the roots of so-called idiographic paleontology. The great American paleontologist Stephen Jay Gould (1941–2002) defined the discipline of idiographic paleontology as illustration and description of the morphological features of extinct species. However, this approach does not investigate macroevolutionary patterns and processes. On the contrary, the paleobiological revolution of the 1970s implemented an epistemic methodology that illustrates macrovelutionary patterns and laws by combining idiographic data with a nomothetic form of (...) explanation. This article elucidates the features of the idiographic data as well as the acquired knowledge coupled with this approach. First of all, Heinrich G. Bronn’s (1800–1862) statistical method is analyzed. Zittel’s practice arose as a reaction against the approximate conclusions reached by Bronn’s quantitative approach. Second, the details of Zittel’s methodology are described in order to bring out its peculiarities. The microscope played a pivotal role in creating and forming Zittel’s morphological data. This analysis sheds new light on the reasons behind the so-called ideographic paleontology, thus revising Gould’s historical reconstruction, as well as on the notion of paleontological data. However, even though Zittel aimed at reaching precise and stable conclusions, his data cannot be used for elucidating evolutionary mechanisms: they are scientific in a purely descriptive sense, but completely useless for biological investigations. Finally, this paper examines how Zittel’s methodology affects the contemporary paleobiological enterprise and thereby reflects upon the notion of natural history. (shrink)

Phylogenies are increasingly being used to investigate human history, diversification and cultural evolution. While using phylogenies in this way is not new, new modes of analysis are being applied to inferring history, reconstructing past states, and examining processes of change. Phylogenies have the advantage of providing a way of creating a continuous history of all current populations, and they make a large number of analyses and hypothesis tests possible even when other forms of historical information are patchy (...) or nonexistent. In common with approaches taken in other historical sciences, phylogenetics is a way of reconstructing past and processes using the traces left in the present day. Trees, based on DNA, language, cultural traits, or other evidence, are now sprouting all over the academic landscape. The increasing use of phylogenetic analysis to understand human cultural evolution has been embraced by some, and scorned by others. The purpose of this article is not to review methods and applications of phylogenetic analyses, nor to consider the growing field of cultural phylogenetics, but, more broadly, to explore how we interpret phylogenies as narratives about human diversification. The first half of the article deals with meaning: phylogenies are often interpreted as histories, but a bifurcating tree is at best an abstract representation of history, and its connections to past events and processes is dependent on the data used, the assumptions made in the analysis, and the degree to which nodes in the tree (where one lineage splits into two) can be connected to change and movement in real populations. The second half of the article explores the purpose of phylogenies: a tree does not have to be a literal history of human lineages in order to be useful for investigating processes of human diversification. Phylogenies should not be read as accurate records of history, but as a way of exploring plausible explanations for current patterns of diversity. Phylogenies provide important information that can be used to test ideas about human diversity, and can help to guard against errors of inference arising from statistical artifacts. (shrink)

Debates over “Big Data” shed more heat than light in the humanities, because the term ascribes new importance to statistical methods without explaining how those methods have changed. What we badly need instead is a conversation about the substantive innovations that have made statistical modeling useful for disciplines where, in the past, it truly wasn’t. These innovations are partly technical, but more fundamentally expressed in what Leo Breiman calls a new “culture” of statistical modeling. Where 20th-century methods (...) often required humanists to squeeze our unstructured texts, sounds, or images into some special-purpose data model, new methods can handle unstructured evidence more directly by modeling it in a high-dimensional space. This opens a range of research opportunities that humanists have barely begun to discuss. To date, topic modeling has received most attention, but in the long run, supervised predictive models may be even more important. I sketch their potential by describing how Jordan Sellers and I have begun to model poetic distinction in the long 19th century—revealing an arc of gradual change much longer than received literary histories would lead us to expect. (shrink)