Through his S–R model of statistical relevance, Wesley Salmon offers a solution to the scientific explanation of objectively improbable events.

This paper argues that a notion of statistical explanation, based on Salmon’s statistical relevance model, can help us better understand deep neural networks. It is proved that homogeneous partitions, the core notion of Salmon’s model, are equivalent to minimal sufficient statistics, an important notion from statistical inference. This establishes a link to deep neural networks via the so-called Information Bottleneck method, an information-theoretic framework, according to which deep neural networks implicitly solve an optimization problem that generalizes minimal sufficient statistics. (...) The resulting notion of statistical explanation is general, mathematical, and subcausal. (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 advance of science and human knowledge is impeded by misunderstandings of various statistics, insufficient reporting of findings, and the use of numerous standardized and non-standardized presentations of essentially identical information. Communication with journalists and the public is hindered by the failure to present statistics that are easy for non-scientists to interpret as well as by use of the word significant, which in scientific English does not carry the meaning of "important" or "large." This article promotes a new standard (...) class='Hi'>method for reporting two-group and two-variable statistics that can enhance the presentation of relevant information, increase understanding of findings, and replace the current presentations of two-group ANOVA, t-tests, correlations, chi-squares, and z-tests of proportions. A brief call to highly restrict the publication of risk ratios, odds ratios, and relative increase in risk percentages is also made, since these statistics appear to provide no useful scientific information regarding the magnitude of findings. (shrink)

Quantitative researchers often discuss research ethics as if specific ethical problems can be reduced to abstract normative logics (e.g., virtue ethics, utilitarianism, deontology). Such approaches overlook how values are embedded in every aspect of quantitative methods, including ‘observations,’ ‘facts,’ and notions of ‘objectivity.’ We describe how quantitative research practices, concepts, discourses, and their objects/subjects of study have always been value-laden, from the invention of statistics and probability in the 1600s to their subsequent adoption as a logic made to appear as (...) if it exists prior to, and separate from, ethics and values. This logic, which was embraced in the Academy of Management from the 1960s, casts management researchers as ethical agents who ought to know about a reality conceptualized as naturally existing in the image of statistics and probability (replete with ‘constructs’), while overlooking that S&P logic and practices, which researchers made for themselves, have an appreciable role in making the world appear this way. We introduce a different way to conceptualize reality and ethics, wherein the process of scientific inquiry itself requires an examination of its own practices and commitments. Instead of resorting to decontextualized notions of ‘rigor’ and its ‘best practices,’ quantitative researchers can adopt more purposeful ways to reason about the ethics and relevance of their methods and their science. We end by considering implications for addressing ‘post truth’ and ‘alternative facts’ problems as collective concerns, wherein it is actually the pluralistic nature of description that makes defending a collectively valuable version of reality so important and urgent. (shrink)

As a contribution to current debates on the ‘social life of methods’, in this article we present an ethnomethodological study of the role of understanding within statistical practice. After reviewing the empirical turn in the methods literature and the challenges to the qualitative-quantitative divide it has given rise to, we argue such case studies are relevant because they enable us to see different ways in which ‘methods’, here quantitative methods, come to have a social life – by embodying and exhibiting (...) understanding they ‘make the social structures of everyday activities observable’ ( Garfinkel, 1967 : 75), thereby putting society on display. Exhibited understandings rest on distinctive lines of practical social and cultural inquiry – ethnographic ‘forays’ into the worlds of the producers and users of statistics – which are central to good statistical work but are not themselves quantitative. In highlighting these non-statistical forms of social and cultural inquiry at work in statistical practice, our case study is an addition to understandings of statistics and usefully points to ways in which studies of the social life of methods might be further developed from here. (shrink)

A general criterion for the theory of belief revision is that when we revise a state of belief by a sentence A, as much of the old information as possible should be retained in the revised state of belief. The motivating idea in this paper is that if a belief B is irrelevant to A, then B should still be believed in the revised state. The problem is that the traditional definition of statistical relevance suffers from some serious shortcomings and (...) cannot be used as a tool for defining belief revision processes. In particular, the traditional definition violates the requirement that if A is irrelevant to C and B is irrelevant to C, then A&B is irrelevant to C. In order to circumvent these drawbacks, I develop an amended notion of relevance which has the desired properties. On the basis of the new definition, I outline how it can be used to simplify a construction of a belief revision method. (shrink)

Multivariate pattern analysis can reveal new information from neuroimaging data to illuminate human cognition and its disturbances. Here, we develop a methodological approach, based on multivariate statistical/machine learning and time series analysis, to discern cognitive processing stages from functional magnetic resonance imaging (fMRI) blood oxygenation level dependent (BOLD) time series. We apply this method to data recorded from a group of healthy adults whilst performing a virtual reality version of the delayed win-shift radial arm maze (RAM) task. This task (...) has been frequently used to study working memory and decision making in rodents. Using linear classifiers and multivariate test statistics in conjunction with time series bootstraps, we show that different cognitive stages of the task, as defined by the experimenter, namely, the encoding/retrieval, choice, reward and delay stages, can be statistically discriminated from the BOLD time series in brain areas relevant for decision making and working memory. Discrimination of these task stages was significantly reduced during poor behavioral performance in dorsolateral prefrontal cortex (DLPFC), but not in the primary visual cortex (V1). Experimenter-defined dissection of time series into class labels based on task structure was confirmed by an unsupervised, bottom-up approach based on Hidden Markov Models. Furthermore, we show that different groupings of recorded time points into cognitive event classes can be used to test hypotheses about the specific cognitive role of a given brain region during task execution. We found that whilst the DLPFC strongly differentiated between task stages associated with different memory loads, but not between different visual-spatial aspects, the reverse was true for V1. Our methodology illustrates how different aspects of cognitive information processing during one and the same task can be separated and attributed to specific brain regions based on information contained in multivariate patterns of voxel activity. (shrink)

The self-avoiding walk is a classical model in statistical mechanics, probability theory and mathematical physics. It is also a simple model of polymer entropy which is useful in modelling phase behaviour in polymers. This monograph provides an authoritative examination of interacting self-avoiding walks, presenting aspects of the thermodynamic limit, phase behaviour, scaling and critical exponents for lattice polygons, lattice animals and surfaces. It also includes a comprehensive account of constructive methods in models of adsorbing, collapsing, and pulled walks, animals and (...) networks, and for models of walks in confined geometries. Additional topics include scaling, knotting in lattice polygons, generating function methods for directed models of walks and polygons, and an introduction to the Edwards model.This essential second edition includes recent breakthroughs in the field, as well as maintaining the older but still relevant topics. New chapters include an expanded presentation of directed models, an exploration of methods and results for the hexagonal lattice, and a chapter devoted to the Monte Carlo methods. (shrink)

With his new riddle of induction, Goodman raised a problem for enumerative induction which many have taken to show that only some ‘natural’ properties can be used for making inductive inferences. Arguably, however, (i) enumerative induction is not a method that scientists use for making inductive inferences in the first place. Moreover, it seems at first sight that (ii) Goodman’s problem does not affect the method that scientists actually use for making such inferences—namely, classical statistics. Taken together, this (...) would indicate that (iii) ‘naturalness’ is not such a relevant concept for the problem of induction, after all. I have no objections against (i) and (iii). But, contrary to (ii), I argue that classical statistics does face a version of Goodman’s problem, which I call the statistical riddle of induction. Given that his problem merely is an instance of the more general problem of underdetermination, this is hardly surprising. Perhaps more importantly, I also show how my riddle can be used for exposing a common fallacy in probabilistic reasoning, without relying on Bayesian assumptions. (shrink)

The article focuses on exploring the directions for implementing innovative analytical-statistical technologies as a tool for monitoring and detecting corruption in the state. To achieve this goal, the author clarifies the content of key concepts, defines the essence of innovative analytical-statistical technologies, and analyzes the applications of these technologies as elements of the state’s anti-corruption policy. It is determined that modern analytical-statistical technologies are integral to information technologies, which have emerged as a separate branch of production known as the information (...) industry. Information technologies, including analytical-statistical ones, are realized through information systems, which combine technical tools (computers, communication devices and channels, peripherals, input/output devices, etc.) with software applications that facilitate the functioning of the technical components and analytical aspects, including the mathematical component (statistics). The use of analytical-statistical technologies as a tool to counter corruption at the state level is driven by the specificity of the corruption identification process. The application of relevant technologies is possible when perceiving corruption as a form of fraud. Therefore, the search for corruption in modern society requires a comprehensive approach, utilizing mathematical, analytical, and psychophysical research methods. This approach enables not only the identification but also the prediction of probable instances of abuse. Five directions for implementing innovative analytical-statistical technologies in anti-corruption activities are identified: 1) automation of data collection and processing; 2) automation of communication and office processes; 3) automation of direct management processes; 4) automation of decision-making processes and development; 5) development of expert systems. It is noted that analytical-statistical technologies find the most implementation in four of the identified directions: data collection/processing, direct management, decision support, and expert support. (shrink)

The article deals with theoretical, practical, partly - historical aspects of scientific research of modern Ukrainian and foreign sociologists and social workers. The aim of the research is to analyze and summarize the following three key aspects: a) historical destructive moments in the development of Ukrainian/Soviet sociology; b) the orientation of the vector of postmodernist research of foreign scholars who had no censorship restrictions on their works; c) the main problematics of current Ukrainian sociological research. The latter, despite their deep (...) materialistic tradition, find opportunities for new non-empirical approaches. In the article with the help of analysis of methodical sources, generalization of their content and presentation and interpretation of individual statistical data the authors substantiate: socio-economic, managerial and pedagogical reasons can systematically present the problematics of the current research of social workers. However, the postmodern aspect, still not "reworked" by the Ukrainian society, has not yet left its final mark on the social research. The international significance of the article lies in the interest of countries of transitional democracies and economies, previously under totalitarian influence, to acquire full emancipation and neo-liberalization concerning social problems and humane ways of solving them. (shrink)

I am very grateful to both Edward Erwin and Peter Fonagy for their thoughtful and engaging comments. I do not have space to deal fully with all the issues they raise, but I will try to clarify some key points at which perhaps I implied more than I intended, or failed to be clear. Erwin states that I claim the following principle is a method for inferring causes: “if X is causally relevant to the occurrence of Y, then the (...) incidence of Ys in the class of Xs and Ys will be different compared with the incidence of Ys in the class of non-Xs and Ys” (Erwin 2012, 217). This is not so. The method I attribute to Grünbaum is given in what follows the principle in the quotation given on p. 199, namely, “To validate a .. (shrink)

Increasingly, clinical research is evaluated on the quality of its statistical analysis. Traditionally, statistical analyses in clinical research have been carried out from a ‘frequentist’ perspective. The presence of an alternative paradigm – the Bayesian paradigm – has been relatively unknown in clinical research until recently. There is currently a growing interest in the use of Bayesian statistics in health care research. This is due both to a growing realization of the limitations of frequentist methods and to the ability of (...) Bayesian methods explicitly to incorporate prior expert knowledge and belief into the analyses. This is in contrast to frequentist methods, where prior experience and beliefs tend to be incorporated into the analyses in an ad hoc fashion. This paper outlines the frequentist and Bayesian paradigms. Acute myocardial infarction mortality data are then analysed from both a Bayesian and a frequentist perspective. In some analyses, the two methods are seen to produce comparable results; in others, they produce different results. It is noted that in this example, there are clinically relevant questions that are more easily addressed from a Bayesian perspective. Finally, areas in clinical research where Bayesian ideas are increasingly common are highlighted. (shrink)

In fMRI research, the goal of correcting for multiple comparisons is to identify areas of activity that reflect true effects, and thus would be expected to replicate in future studies. Finding an appropriate balance between trying to minimize false positives (Type I error) while not being too stringent and omitting true effects (Type II error) can be challenging. Furthermore, the advantages and disadvantages of these types of errors may differ for different areas of study. In many areas of social neuroscience (...) that involve complex processes and considerable individual differences, such as the study of moral judgment, effects are typically smaller and statistical power weaker, leading to the suggestion that less stringent corrections that allow for more sensitivity may be beneficial, but also result in more false positives. Using moral judgment fMRI data, we evaluated four commonly used methods for multiple comparison correction implemented in SPM12 by examining which method produced the most precise overlap with results from a meta-analysis of relevant studies and with results from nonparametric permutation analyses. We found that voxel-wise thresholding with family-wise error correction based on Random Field Theory provides a more precise overlap (i.e., without omitting too few regions or encompassing too many additional regions) than either clusterwise thresholding, Bonferroni correction, or false discovery rate correction methods. (shrink)

Causal modeling methods such as path analysis, used in the social and natural sciences, are also highly relevant to philosophical problems of probabilistic causation and statistical explanation. We show how these methods can be effectively used (1) to improve and extend Salmon's S-R basis for statistical explanation, and (2) to repair Cartwright's resolution of Simpson's paradox, clarifying the relationship between statistical and causal claims.

Conflicting results undermine making inferences from the empirical literature. So far, the replication crisis is mainly seen as resulting from honest errors and questionable research practices such as p-hacking or the base-rate fallacy. I discuss the malleability (researcher degrees of freedom) of quantitative research and argue that conflicting results can emerge from two studies using different but plausible designs (e.g., eligibility criteria, operationalization of concepts, outcome measures) and statistical methods. I also explore how the choices regarding study design and statistical (...) techniques bias results in a way that makes them more or less relevant for a given policy or clinical question. (shrink)

Arrow's Independence of Irrelevant Alternatives Condition is examined. It is shown why the standard rationale for (or against) the condition tends to be inconclusive as it fails to consider the basic ‘game’ issue in social choice. Specifically it is explained how some recent results (Gibbard-Satterthwaite) on the general non-existence of strategy-proof voting procedures provide the strongest rationale for the independence condition. Also, it is shown that this rationale was exactly the one used by Condorcet in his work on decision rules (...) for juries and elections. (shrink)

Background: Mental healthcare needs person-tailored interventions. Experience Sampling Method (ESM) can provide daily life monitoring of personal experiences. This study aims to operationalize and test a measure of momentary reward-related Quality of Life (rQoL). Intuitively, quality of life improves by spending more time on rewarding experiences. ESM clinical interventions can use this information to coach patients to find a realistic, optimal balance of positive experiences (maximize reward) in daily life. rQoL combines the frequency of engaging in a relevant context (...) (a ‘behavior setting’) with concurrent (positive) affect. High rQoL occurs when the most frequent behavior settings are combined with positive affect or infrequent behavior settings co-occur with low positive affect. Methods: Resampling procedures (Monte Carlo experiments) were applied to assess the reliability of rQoL using various behavior setting definitions under different sampling circumstances, for real or virtual subjects with low-, average- and high contextual variability. Furthermore, resampling was used to assess whether rQoL is a distinct concept from positive affect. Virtual ESM beep datasets were extracted from 1058 valid ESM observations for virtual and real subjects. Results: Behavior settings defined by Who-What contextual information were most informative. Simulations of at least 100 ESM observations are needed for reliable assessment. Virtual ESM beep datasets of a real subject can be defined by Who-What-Where behavior setting combinations. Large sample sizes are necessary for reliable rQoL assessments, except for subjects with low contextual variability. rQoL is distinct from positive affect. Conclusion: rQoL is a feasible concept. Monte Carlo experiments should be used to assess the reliable implementation of an ESM statistic. Future research in ESM should asses the behavior of summary statistics under different sampling situations. This exploration is especially relevant in clinical implementation, where often only small datasets are available. (shrink)

The angular momentum operators for a system of two spin-zero indistinguishable particles are constructed, using Isham’s Canonical Group Quantization method. This mathematically rigorous method provides a hint at the correct definition of (total) angular momentum operators, for arbitrary spin, in a system of indistinguishable particles. The connection with other configuration space approaches to spin-statistics is discussed, as well as the relevance of the obtained results in view of a possible alternative proof of the spin-statistics theorem.

This essay demonstrates a previously unnoticed connection between formal and statistical learning theory with regard to Nelson Goodman’s new riddle of induction. Discussions of Goodman’s riddle in formal learning theory explain how conjecturing “all green” before “all grue” can enhance efficient convergence to the truth, where efficiency is understood in terms of minimizing the maximum number of retractions or “mind changes.” Vapnik-Chervonenkis (VC) dimension is a central concept in statistical learning theory and is similar to Popper’s notion of degrees of (...) testability. I show that for a class inductive problems of which Goodman’s riddle is one example, a reliable inductive method minimizes the maximum number of mind changes exactly if it always conjectures the hypothesis from the set with lowest VC dimension consistent with the data. I also discuss the relevance of these results to language invariance and curve fitting. (shrink)

The abbreviation ARCS in the ARCS motivational model comprises the first letters of four English words: Attention, Relevance, Confidence, and Satisfaction. The ARCS motivation model is based on a systematic and easy-to-operate motivation theory. Many research studies have verified the applicability and effectiveness of the ARCS model in education worldwide. The proposed optimized ARCS motivation model takes the traditional ARCS motivation model and systematically optimizes it to make it suitable for the coding of data from videos of music classes. The (...) case analysis method selected 14 high-quality music lessons as the research object. The optimized ARCS model involves text conversion, coding, and statistical analysis of the transcripts of videos of high-quality music classes. The data analysis was used to analyze the characteristics of students’ emotional and behavioral motivation incentive strategies in each section of the ARCS motivation model in combination with specific high-quality case lesson fragments. This paper summarizes ways and means of using a motivational approach in the teaching of quality music classes, providing theoretical support for the practice of music teaching. (shrink)

Background In the early stages of the COVID-19 pandemic, many health systems, including those in the UK, developed triage guidelines to manage severe shortages of ventilators. At present, there is an insufficient understanding of how the public views these guidelines, and little evidence on which features of a patient the public believe should and should not be considered in ventilator triage. Methods Two surveys were conducted with representative UK samples. In the first survey, 525 participants were asked in an open-ended (...) format to provide features they thought should and should not be considered in allocating ventilators for COVID-19 patients when not enough ventilators are available. In the second survey, 505 participants were presented with 30 features identified from the first study, and were asked if these features should count in favour of a patient with the feature getting a ventilator, count against the patient, or neither. Statistical tests were conducted to determine if a feature was generally considered by participants as morally relevant and whether its mean was non-neutral. Results In Survey 1, the features of a patient most frequently cited as being morally relevant to determining who would receive access to ventilators were age, general health, prospect of recovery, having dependents, and the severity of COVID symptoms. The features most frequently cited as being morally irrelevant to determining who would receive access to ventilators are race, gender, economic status, religion, social status, age, sexual orientation, and career. In Survey 2, the top three features that participants thought should count in favour of receiving a ventilator were pregnancy, having a chance of dying soon, and having waited for a long time. The top three features that participants thought should count against a patient receiving a ventilator were having committed violent crimes in the past, having unnecessarily engaged in activities with a high risk of COVID-19 infection, and a low chance of survival. Conclusions The public generally agreed with existing UK guidelines that allocate ventilators according to medical benefits and that aim to avoid discrimination based on demographic features such as race and gender. However, many participants expressed potentially non-utilitarian concerns, such as inclining to deprioritise ventilator allocation to those who had a criminal history or who contracted the virus by needlessly engaging in high-risk activities. (shrink)

In the autumn of 1959, Arne Naess and J. L. Austin, both pioneers of empirical study in the philosophy of language, discussed their points of agreement and disagreement at a meeting in Oslo. This article considers the fragmentary record that has survived of that meeting, and investigates what light it can shed on the question of why the two philosophers apparently found so little common ground, given their shared commitment to the importance of data in the study of language. Naess (...) and Austin held different views about two significant aspects of the relationship between scientific method and philosophical investigation. The first aspect concerns the nature of experimental data; Naess used the statistical analysis of data collected from non-philosophical informants while Austin advocated deliberation leading to agreement over usage by a few skilled experts. The second aspect relates to their respective attitudes to the role of theory in philosophical inquiry, attitudes which drew on discussions of scientific method, and its relevance to philosophy, from the early decades of the twentieth century. This article traces the evidence for these views on scientific method in Naess’s and Austin’s respective published work, and in the record of their Oslo meeting. It concludes with a brief overview of opinions about scientific method manifest in the decades since that meeting in various branches of linguistics. These opinions speak to the enduring importance of attitudes to scientific method in relation to our study and understanding of human language. (shrink)

Evidential pluralists, like Federica Russo and Jon Williamson, argue that causal claims should be corroborated by establishing both the existence of a suitable correlation and a suitable mechanism complex. At first glance, this fits well with mixed method research in the social sciences, which often involves a pluralist combination of statistical and mechanistic evidence. However, statistical evidence concerns a population of cases, while mechanistic evidence is found in individual case studies. How should researchers combine such general statistical evidence and (...) specific mechanistic evidence? This article discusses a very recent answer to this question, ‘multi-method large-N qualitative analysis’ or multi-method LNQA, popular in political science and international relations studies of rare events like democratic transitions and cease-fire agreements. Multi-method LNQA combines a comprehensive study of all relevant event cases with statistical analysis, in an attempt to solve the issues of generalization faced by other types of qualitative research, such as selection bias and lack of representativeness. I will argue that the kind of general causal claim that multi-method LNQA is after, however, is crucially different from the average treatment effect found in statistical analysis and can in fact only be supported with mechanistic evidence. I conclude from this that mixed method research, and thereby evidential pluralism, may be inappropriate in this context. (shrink)

Probabilistic inference from frequencies, such as "Most Quakers are pacifists; Nixon is a Quaker, so probably Nixon is a pacifist" suffer from the problem that an individual is typically a member of many "reference classes" (such as Quakers, Republicans, Californians, etc) in which the frequency of the target attribute varies. How to choose the best class or combine the information? The article argues that the problem can be solved by the feature selection methods used in contemporary Big Data science: the (...) correct reference class is that determined by the features relevant to the target, and relevance is measured by correlation (that is, a feature is relevant if it makes a difference to the frequency of the target). (shrink)

On the basis of analyzing the complexity of railway flatcar loading optimization problem, according to the characteristics of railway flatcar loading, based on the situation of railway transport loading unit of multiple railway flatcars, this study puts forward the optimal loading optimization method of multimodel railway flatcars based on improved genetic algorithm, constructs the linear programming model of railway flatcar loading optimization problem, and combines with the improved genetic algorithm to solve the problem. The study also analyzes the structural (...) characteristics of the optimal loading materials of multimodel railway flatcars, selects the optimal materials and inputs the relevant data into the computer, and uses MATLAB to program the optimal loading algorithm of multimodel railway flatcars. Through the analysis of the calculation example, the study discusses its scope of application. The experimental results show that the average general utilization rate of the proposed method is 73%, which has higher universality, more effective application, and fully meets the research requirements. It is verified that the proposed method has a statistically significant impact on the optimal loading of multi-type railway flatcars. (shrink)

This paper considers the possibility of prediction in land use planning, and the use of statistical research methods in analyses of relationships between urban form and travel behaviour. Influential writers within the tradition of critical realism reject the possibility of predicting social phenomena. This position is fundamentally problematic to public planning. Without at least some ability to predict the likely consequences of different proposals, the justification for public sector intervention into market mechanisms will be frail. Statistical methods like regression analyses (...) are commonly seen as necessary in order to identify aggregate-level effects of policy measures, but are questioned by many advocates of critical realist ontology. Using research into the relationship between urban structure and travel as an example, the paper discusses relevant research methods and the kinds of prediction necessary and possible in spatial planning of urban development. Finally, the political implications of positions within theory of science rejecting the possibility of predictions about social phenomena are addressed. (shrink)

A major problem for interpersonal aggregation is how to compare utility across individuals; a major problem for decision-making under normative uncertainty is the formally analogous problem of how to compare choice-worthiness across theories. We introduce and study a class of methods, which we call statistical normalization methods, for making interpersonal comparisons of utility and intertheoretic comparisons of choice-worthiness. We argue against the statistical normalization methods that have been proposed in the literature. We argue, instead, in favor of normalization of variance: (...) we claim that this is the account that most plausibly gives all individuals or theories ‘equal say’. To this end, we provide two proofs that variance normalization has desirable properties that all other normalization methods lack, though we also show how different assumptions could lead one to axiomatize alternative statistical normalization methods. (shrink)

Integrating RDF datasets has become a relevant problem for both researchers and practitioners. In the literature, there are many genetic proposals that learn rules that allow to link the resources that refer to the same real-world entities, which is paramount to integrating the datasets. Unfortunately, they are context-unaware because they focus on the resources and their attributes but forget about their neighbours. This implies that they fall short in cases in which different resources have similar attributes but refer to different (...) real-world entities or cases in which they have dissimilar attributes but refer to the same real-world entities. In this article, we present a proposal that learns context-aware rules that take into account both the attributes of the resources and their neighbours. We have conducted an extensive experimentation that proves that it outperforms the most advanced genetic proposal. Our conclusions were checked using statistically sound methods. (shrink)

Numerous philosophers, among them Carl G. Hempel and Wesley C. Salmon, have attempted to explicate the notion of explanatory relevance in terms of the statistical relevance of various properties of an individual to the explanandum property itself (or what is here called narrow statistical relevance). This approach seems plausible if one assumes that to explain an occurrence is to show that it was to be expected or to exhibit its degree of expectability and the factors which influence its expectability. But (...) considerations of narrow statistical relevance do not provide an adequate basis for explanatory classification, and the aforementioned views of explanation are accordingly mistaken. Explanatory classification must provide at least a partial account of the nature of a thing, and such an account will generally go beyond what is required as a basis for correct expectation. (shrink)

With an increased emphasis on upstream activity and Defence Engagement, it has become increasingly more important for the UK Ministry of Defence (MOD) and government to understand the relationship between conflict and regional instability. As part of this process, the Historical and Operational Data Analysis Team (HODA) in Defence Science and Technology Laboratory (Dstl) was tasked to look at factors that influenced the regional spread of internal conflicts to help aid the decision making of government. Conflict contagion is the process (...) by which a conflict in one state (State A) influences the outbreak of conflict in another state (State B). The aim of looking at these factors was to produce a tool to assist in the cost/benefit analysis of intervening in future conflicts. The task was carried out by quantitatively studying a selection of contagion and non-contagion case studies over a set of 14 numerical variables that covered structural, political, socioeconomic and cultural factors of both States A and B. All case studies took place after the end of the Cold War. The dataset used contained both binary and continuous data. A range of statistical techniques were used including correlation, regression and principal component analyses along with graphical analytical methods. Unfortunately creating a tool to predict contagion has proven difficult and so the scope of the study was changed-as no statistically relevant link was found. However, it was shown that some links do exists between the variables and the existence of contagion, and it also appears it is a combination of variables which has an effect on the likelihood of contagion. Conflict contagion is a rare event and was only recorded in less than 1% of cases present in the dataset. Of the variables analysed, the most significant factor was the number of refugees present in State B who originated in State A for the year before the case study. It is recommended that further work be conducted. It is possible that a more detailed investigation, using a broader range of techniques and/or a wider selection of variables might be successful in assessing the likelihood of conflict contagion. (shrink)

Scientific explanation is an important goal of scientific practise. Philosophers have proposed a striking diversity of seemingly incompatible accounts of explanation, from deductive-nomological to statistical relevance, unification, pragmatic, causal-mechanical, mechanistic, causal intervention, asymptotic, and model-based accounts. In this dissertation I apply two novel methods to reexamine our evidence about scientific explanation in practise and thereby address the fragmentation of philosophical accounts. I start by collecting a data set of 781 articles from one year of the journal Science. Using automated text (...) mining techniques I measure the frequency and distribution of several groups of philosophically interesting words, such as "explain", "cause", "evidence", "theory", "law", "mechanism", and "model". I show that "explain" words are much more common in scientific writing than in other genres, occurring in roughly half of all articles, and that their use is very often qualified or negated. These results about the use of words complement traditional conceptual analysis. Next I use random samples from the data set to develop a large number of small case studies across a wide range of scientific disciplines. I use a sample of "explain" sentences to develop and defend a new general philosophical account of scientific explanation, and then test my account against a larger set of randomly sampled sentences and abstracts. Five coarse categories can classify the explanans and explananda of my cases: data, entities, kinds, models, and theories. The pair of the categories of the explanans and explanandum indicates the "form" of an explanation. The explain-relation supports counterfactual reasoning about the dependence of qualities of the explanandum on qualities of the explanans. But for each form there is a different "core relation" between explanans and explanandum that supports the explain-relation. Causation, modelling, and argument are the core relations for different forms of scientific explanation between different categories of explanans and explananda. This flexibility allows me to resolve some of the fragmentation in the philosophical literature. I provide empirical evidence to show that my general philosophical account successfully describes a wide range of scientific practise across a large number of scientific disciplines. (shrink)

In Salmon's discussion of his account of statistical relevance and statistical explanation there is a peculiarity in the selection of examples. Where he wishes to show that statistical accounts are reasonably treated as explanatory, he draws examples from the social sciences, such as juvenile delinquency. But when he explains the concept of 'causal' relevance, the examples are selected from the natural sciences. This conceals difficulties with salmon's account of causality in the face of multiple causes such as are characteristic of (...) the social sciences. Salmon's account is shown not to escape difficulties associated with Simon's earlier approach. (shrink)

According to influential accounts of scientific method, such as critical rationalism, scientific knowledge grows by repeatedly testing our best hypotheses. But despite the popularity of hypothesis tests in statistical inference and science in general, their philosophical foundations remain shaky. In particular, the interpretation of non-significant results—those that do not reject the tested hypothesis—poses a major philosophical challenge. To what extent do they corroborate the tested hypothesis, or provide a reason to accept it? Popper sought for measures of corroboration that (...) could adequately answer this question. According to Popper, corroboration is different from probability-raising, and grounded in the predictive success and testability of a hypothesis. As such, corroboration becomes an indicator of the scientific value of a hypothesis and guides our practical preferences over hypotheses that have been subjected to severe tests. This article proves two impossibility results for corroboration measures based on statistical relevance. The generality of these results shows that Popper’s qualitative characterization of corroboration must be misguided. I explore what a more promising and scientifically useful concept of corroboration could look like. (shrink)

Structural equation model is a multivariate statistical analysis method. It can not only test some unpredictable abstract ideas, but also design parameters for the causal connection model between independent variables and dependent variables. Among them, the analysis of various latent variables is based on the verification factor analysis technology. The research first collects various relevant data, derives the latent variables and measurement variables, then composes the measurement model, and then verifies the adaptability of the measurement model structure mode through (...) actual data collection. When such suitable factors are determined, a causal model based on path analysis technology for latent variables, that is, a structural model, can be used for parameter design. This article uses the structural equation model as an analysis tool, starting from the three aspects of teachers, cases, and students to evaluate the application effect of the case teaching method in the classroom teaching of intellectual property law course and construct a structural equation model of the influencing factors of the case teaching effect. To understand students’ satisfaction with case teaching effects and related influencing factors, the research results show that the effect of case teaching is jointly affected by the level of teachers, case selection, and student response. Among them, teacher factors have the greatest impact on case teaching effects, followed by case factors, and students have the least. (shrink)

It is probable that, increasingly, genome investigations are going to be based on statistical formalization. This review summarizes the state of art and potentiality of using statistics in microbial genome analysis. First, I focus on recent advances in functional genomics, such as finding genes and operons, identifying gene conversion events, detecting DNA replication origins and analysing regulatory sites. Then I describe how to use phylogenetic methods in genome analysis and methods for genome‐wide scanning for positively selected amino acids. I conclude (...) with speculations on the future course of genome statistical modeling. BioEssays 25:266–273, 2003. © 2003 Wiley Periodicals, Inc. (shrink)

A new variational method, the principle of least radix economy, is formulated. The mathematical and physical relevance of the radix economy, also called digit capacity, is established, showing how physical laws can be derived from this concept in a unified way. The principle reinterprets and generalizes the principle of least action yielding two classes of physical solutions: least action paths and quantum wavefunctions. A new physical foundation of the Hilbert space of quantum mechanics is then accomplished and it is (...) used to derive the Schrödinger and Dirac equations and the breaking of the commutativity of spacetime geometry. The formulation provides an explanation of how determinism and random statistical behavior coexist in spacetime and a framework is developed that allows dynamical processes to be formulated in terms of chains of digits. These methods lead to a new foundation for Lorentz transformations and special relativity. The Parker-Rhodes combinatorial hierarchy is encompassed within our approach and this leads to an estimate of the interaction strength of the electromagnetic and gravitational forces that agrees with the experimental values to an error of less than one thousandth. Finally, it is shown how the principle of least-radix economy naturally gives rise to Boltzmann’s principle of classical statistical thermodynamics. A new expression for a general nonequilibrium entropy is proposed satisfying the Second Law of Thermodynamics. (shrink)

The relevance of this study's topic is supported by the argument that a philosophical understanding of the fundamental concepts of epistemology as they pertain to the educational process is crucial as the educational setting becomes increasingly digitalised. This paper aims to explore the epistemological component of the philosophy of learning in light of the educational process digitalisation. The research comprised a sample of 462 university students from Kazakhstan, with 227 participants assigned to the experimental and 235 to the control groups. (...) The research employed a scientific methodology that encompassed various scientific methods, including sociological, socio-philosophical, and culturological analysis. In addition, philosophical methods such as system analysis, structural and functional analysis, and comparative and hermeneutical approaches were utilised for the philosophical and epistemological interpretation of the cognitive activity mechanism of students and its dynamics in light of digitalising education. Furthermore, psychological diagnostic methods such as SAMOAL personality self-actualisation diagnostics, personality volitional potential diagnostics, and psychodiagnostic methods were employed. This study offers a theoretical rationale for the integration of digital technology in the realm of education, grounded in philosophical and epistemological principles. In addition, it challenges the null hypothesis that the philosophical and epistemological framework of the educational process does not influence its cognitive and personal aspects. Digital learning has been found to improve both cognitive and personal aspects of the learning process. All indicators of self-realization increased statistically significantly (p 0.05). The positive impact of digital technologies on increasing the communicative competence of students can be considered as a factor in mitigating epistemic risks in the learning process.The findings can be used to avoid epistemological risks and improve learning effectiveness in a digital learning environment. There are plans to investigate the gender dimension of digital learning epistemology in the future. (shrink)

The relevance of the research In the face of increasing global competition, business was challenged to seek new methods for creating their competitive advantage and at the same time the decreasing budgets of higher education institutions were pressured to find new streams of financing. In both cases, collaboration is seen as an important method for achieving their objectives but universities of today have as well to find the appropriate balance between teaching, basic and applied research, and entrepreneurship. Ten types (...) of university-business collaboration are related quite directly to the missions of the university and the needs of business. Curriculum development and delivery is one of that ten, which aim is to develop human resources to modern society. A summary of benefits was identified in the academic literature as arising from UBC in relation to curriculum design and delivery for multiple stakeholders including academics, students, university administration, business and community. Overall, UBC may take various forms that are influenced by different factors but even if all stakeholders seeks the main purpose of this process they may get different benefits. The research aim was to identify the benefits of universities and business organizations in curriculum development. The objectives of the research: to determine the instruments and activities used for universities and business organizations collaboration, to identify universities and business organizations benefits from collaboration to the various stakeholder groups. Analysis of recent research and publications. UBC became the subject of education and management sciences. P. D'Este and M. Perkmann explored the factors of UBC, the types were identified by T. Davey, T. Baaken, V. Galan Muros, A. Meerman, T. Barnes, A. Gibbons and the levels of UBC were represented by B.N. Ponomariov, P.C. Boardman, T. Davey, R. Laužackas. The benefits of UBC to research quality have been studied by researchers T. Davey, M. Crespo, N. Carayol, H. Forsyth, R. Laxton, S. Lamichhane, T. Nath Sharma, P. Van der Sijde and H. Dridi, as a collaborative factor for learning improvement by researchers K. Ramakrishnan, N.M. Yasin, A. Draghici. An overview of the study of this object shows that it was mostly analysed in vocational training and in last ten years’ period the publications is growing in UBC. Research methodology. The paper seeks to represent the UBC benefits for different stakeholders and collaboration forms, which was used by university with the business organizations from leisure industry. Quantitative research was used to gain quantify opinions of benefits and instruments of UBC – and generalize results from a larger sample population. Methods applied for the research was scientific literature review, a questionnaire survey for business organization leaders and mathematical statistics. Conclusion. The benefits of the UVB were grouped according to the type of stakeholder's: society, university administration, academics, entrepreneurs, students. The benefits of business stakeholders include additional funding, access to education resources, lecturer and coordinator, support in evaluating the program and developing new study subjects. The highest rated benefit to others stakeholders from their view could be reducing academic staff training costs, as well as business information available to student projects, skills development and student employment opportunities and human resource development in the region. (shrink)

In this paper I critically examine the Generality Problem and argue that it does not succeed as an objection to reliabilism. Although those who urge the Generality Problem are correct in claiming that any process token can be given indefinitely many descriptions that pick out indefinitely many process types, they are mistaken in thinking that reliabilists have no principled way to distinguish between relevant and irrelevant process types.

Explanation is a central concept in human psychology. Drawing upon philosophical theories of explanation, psychologists have recently begun to examine the relationship between explanation, probability and causality. Our study advances this growing literature in the intersection of psychology and philosophy of science by systematically investigating how judgments of explanatory power are affected by the prior credibility of a potential explanation, the causal framing used to describe the explanation, the generalizability of the explanation, and its statistical relevance for the evidence. Collectively, (...) the results of our five experiments support the hypothesis that the prior credibility of a causal explanation plays a central role in explanatory reasoning: first, because of the presence of strong main effects on judgments of explanatory power, and second, because of the gate-keeping role it has for other factors. Highly credible explanations were not susceptible to causal framing effects. Instead, highly credible hypotheses were sensitive to the effects of factors which are usually considered relevant from a normative point of view: the generalizability of an explanation, and its statistical relevance for the evidence. These results advance current literature in the philosophy and psychology of explanation in three ways. First, they yield a more nuanced understanding of the determinants of judgments of explanatory power, and the interaction between these factors. Second, they illuminate the close relationship between prior beliefs and explanatory power. Third, they clarify the relationship between abductive and probabilistic reasoning. (shrink)

The relevance of the research is that university and business collaboration is the main implementation tool of the third university mission. University-business collaboration has risen to one of the top priorities for many higher education institutions, with its importance mirroring attention from scholars and policy makers worldwide. In the face of increasing global competition, business was challenged to seek new methods for creating their competitive advantage and at the same time, the decreasing budgets of higher education institutions were pressured to (...) find new streams of financing. In both cases, collaboration in different forms is an important method for achieving their objectives. Ten types of UBC are related quite directly to the missions of the university and the needs of business but one of them curriculum development and delivery is very important. Using this form for UBC, could help to develop human resources relevant to modern society. The main instruments and activities in this form of collaboration as identified by business is too little used. The research aim was to identify the activities of university and leisure organizations used for collaboration in curriculum development. The objectives of the research: to determine the forms of UBC, to identify the activities used for universities and leisure organizations collaboration in curriculum development. Analysis of recent research and publications. UBC became the subject of education and management sciences. Recently, much attention has been paid to UBC collaboration practices especially a lot of research on practices was done about universities collaboration in R&D and commercialisation of R&D. P. D'Este and M. Perkmann explored the factors of UBC, the types were identified by T. Davey, T. Baaken, V. Galan Muros, A. Meerman, T. Barnes, A. Gibbons and the levels of UBC were represented by B.N. Ponomariov, P.C. Boardman, T. Davey. The benefits of UBC to research quality have been studied by researchers M. Crespo and H. Dridi, as a collaborative factor for learning improvement by researchers K. Ramakrishnan, N.M. Yasin, A. Draghici, as a quality factor UBC was analysed by M. Perkmann, Z. King, S. Pavelin. The main researchers who analysed the UBC in curriculum development was the T. Davey, A. Healy, C. Plewa, T. Baaken. An overview of the study of this object shows that it was mostly analysed in vocational training and in last ten years’ period the publications is growing in UBC. Research methodology. The paper seeks to represent the collaboration forms, which was used by university with the business organizations from leisure industry. As well, it seeks to identify the activities of business collaboration in curriculum design, development and evaluation. Methods applied for the research was scientific literature review, a questionnaire survey for business organization leaders and mathematical statistics. Conclusion. The results of business organizations show the positive impact for increasing the university collaboration as a hole but in study programs, curriculum development shows that it is needed more business engagement. With the business engagement into curriculum academics, expect to be given the opportunity to transfer theoretical ideas into practical projects and to implement research in the real world. At the same time, the business engage in the curriculum development mostly through giving guest’s lectures and consultations, place for practice, or organizing the different events with the academics. (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)

In discussions of the power of causal explanations, one often finds a commitment to two premises. The first is that, all else being equal, a causal explanation is powerful to the extent that it cites the full causal history of why the effect occurred. The second is that, all else being equal, causal explanations are powerful to the extent that the occurrence of a cause allows us to predict the occurrence of its effect. This article proves a representation theorem showing (...) that there is a unique family of functions measuring a causal explanation’s power that satisfies these two premises. (shrink)

Machine learning and statistical methods have yielded impressive results in a wide variety of natural language processing tasks. These advances have generally been regarded as engineering achievements. In fact it is possible to argue that the success of machine learning methods is significant for our understanding of the cognitive basis of language acquisition and processing. Recent work in unsupervised grammar induction is particularly relevant to this issue. It suggests that knowledge of language can be achieved through general learning procedures, and (...) that a richly articulated language faculty is not required to explain its acquisition. (shrink)