scholarly journals Bayesian Reasoning’s Power to Challenge Religion and Empirically Justify Atheism

2021 ◽  
Vol 3 (1) ◽  
pp. 75-95
Author(s):  
Richard Carrier
Keyword(s):  
Bayes Theorem ◽  
Mathematical Equation ◽  
Empirical Argument ◽  
Original Argument

Bayes’ Theorem is a simple mathematical equation that can model every empirical argument. Accordingly, once understood it can be used to analyze, criticize, or improve any argument in matters of fact. By extension, it can substantially improve an overall argument for atheism (here meaning the belief that supernatural gods probably do not exist) by revealing that god apologetics generally operates through the omission of evidence, and how every argument for there being a god becomes an argument against there being a god once you reintroduce all the pertinent evidence that the original argument left out. This revelation further reveals that god apologetics generally operates through the omission of evidence. This paper demonstrates these propositions by illustrating their application with examples.

Bayesian Applications in Auditory Research

2019 ◽  
Vol 62 (3) ◽  
pp. 577-586 ◽  
Author(s):  
Garnett P. McMillan ◽  
John B. Cannon
Keyword(s):  
Monte Carlo ◽  
Markov Chain ◽  
Bayesian Methods ◽  
Prior Distribution ◽  
Interim Analysis ◽  
Iterative Process ◽  
Bayes Theorem ◽  
Sound Therapy ◽  
The Many ◽  
Auditory Research

Purpose This article presents a basic exploration of Bayesian inference to inform researchers unfamiliar to this type of analysis of the many advantages this readily available approach provides. Method First, we demonstrate the development of Bayes' theorem, the cornerstone of Bayesian statistics, into an iterative process of updating priors. Working with a few assumptions, including normalcy and conjugacy of prior distribution, we express how one would calculate the posterior distribution using the prior distribution and the likelihood of the parameter. Next, we move to an example in auditory research by considering the effect of sound therapy for reducing the perceived loudness of tinnitus. In this case, as well as most real-world settings, we turn to Markov chain simulations because the assumptions allowing for easy calculations no longer hold. Using Markov chain Monte Carlo methods, we can illustrate several analysis solutions given by a straightforward Bayesian approach. Conclusion Bayesian methods are widely applicable and can help scientists overcome analysis problems, including how to include existing information, run interim analysis, achieve consensus through measurement, and, most importantly, interpret results correctly. Supplemental Material https://doi.org/10.23641/asha.7822592

Outcome – Studien im Zusammenhang mit Laboranalysen

2015 ◽  
Vol 72 (2) ◽  
pp. 93-98
Author(s):  
Andreas R. Huber
Keyword(s):  
Bayes Theorem ◽  
Wird Eine ◽  
Psa Test

Biochemische Erkenntnisse und das Wissen über Stoffwechselvorgänge bis zum einzelnen Molekül und die rasche Entwicklung von neuen, sehr leistungsfähigen Methoden haben es erlaubt, dass die Labormedizin als wichtiger Bestandteil von Diagnose, Ausschluss, Therapie, Monitoring und als prädiktiver Test Einzug in die Medizin erhalten hat. Wichtig ist nicht nur die Qualität des Assays, sondern auch das Fachwissen um den Test, d. h. dass ein Test für die richtige Fragestellung eingesetzt wird und die Wertigkeit dem Kliniker bekannt ist. Hinzu kommen das Einhalten der präanalytischen Bedingungen, Kenntnisse über statistische Fakten wie Bayes Theorem und der gekonnte Miteinbezug anderer Resultate, klinischer Gegebenheiten. So lässt sich Berechnung oder wenigstens Abschätzung einer postanalytischen Wahrscheinlichkeit erheben. Der gleiche Test wird eine sehr unterschiedliche Performance haben je nach dem gewählten Einsatzort, resp. dem gewählten Patientenkollektiv. So macht z. B. ein erstmaliger PSA-Test bei einem 70-jährigen Patienten wenig Sinn. Weiter spielen auch die Qualitäten des Tests eine entscheidende Rolle. Es kann davon ausgegangen werden, dass gerade in der Labormedizin weitere Outcome-Studien folgen werden. Der Wert dieser nimmt zu, da die Tests in der Regel nicht bis wenig invasiv, relativ günstig und rasch erhältlich sind.

Effects of Observer Variation on Performance in Probabilistic Diagnosis of Jaundice

1981 ◽  
Vol 20 (03) ◽  
pp. 163-168 ◽  
Author(s):  
G. Llndberg
Keyword(s):  
Physical Examination ◽  
System Performance ◽  
Transition Matrix ◽  
Bayes Theorem ◽  
Observer Variation ◽  
Kappa Statistics ◽  
Diagnostic Categories ◽  
Number Of Patients ◽  
Probability Transition Matrix ◽  
Probabilistic Diagnosis

A system for probabilistic diagnosis of jaundice has been used for studying the effects of taking into account the unreliability of diagnostic data caused by observer variation. Fourteen features from history and physical examination were studied. Bayes’ theorem was used for calculating the probabilities of a patient’s belonging to each of four diagnostic categories.The construction sample consisted of 61 patients. An equal number of patients were tested in the evaluation sample. Observer variation on the fourteen features had been assessed in two previous studies. The use of kappa-statistics for measuring observer variation allowed the construction of a probability transition matrix for each feature. Diagnostic probabilities could then be calculated with and without the inclusion of weights for observer variation. Tests of system performance revealed that discriminatory power remained unchanged. However, the predictions rendered by the variation-weighted system were diffident. It is concluded that taking observer variation into account may weaken the sharpness of probabilistic diagnosis but it may also help to explain the value of probabilistic diagnosis in future applications.

Bayesian Diagnostic Probabilities without Assuming Independence of Symptoms

1991 ◽  
Vol 30 (01) ◽  
pp. 15-22 ◽  
Author(s):  
A. Gammerman ◽  
A. R. Thatcher
Keyword(s):  
Abdominal Pain ◽  
Acute Abdominal Pain ◽  
Final Diagnosis ◽  
Bayes Theorem ◽  
Bayes Method ◽  
Hospital Records ◽  
Computer Diagnosis ◽  
Bayes Model ◽  
Chi Squared ◽  
Past Data

The paper describes an application of Bayes’ Theorem to the problem of estimating from past data the probabilities that patients have certain diseases, given their symptoms. The data consist of hospital records of patients who suffered acute abdominal pain. For each patient the records showed a large number of symptoms and the final diagnosis, to one of nine diseases or diagnostic groups. Most current methods of computer diagnosis use the “Simple Bayes” model in which the symptoms are assumed to be independent, but the present paper does not make this assumption. Those symptoms (or lack of symptoms) which are most relevant to the diagnosis of each disease are identified by a sequence of chi-squared tests. The computer diagnoses obtained as a result of the implementation of this approach are compared with those given by the “Simple Bayes” method, by the method of classification trees (CART), and also with the preliminary and final diagnoses made by physicians.

War in Social Thought

2012 ◽  
Author(s):  
Hans Joas ◽  
Wolfgang Knöbl
Keyword(s):  
Twentieth Century ◽  
Intellectual History ◽  
Large Scale ◽  
Theoretical Work ◽  
German Idealism ◽  
Social Thought ◽  
Social Progress ◽  
Modern World ◽  
Critical History ◽  
Original Argument

This book provides a sweeping critical history of social theories about war and peace from Thomas Hobbes to the present. It presents both a broad intellectual history and an original argument as it traces the development of thinking about war over more than 350 years—from the premodern era to the period of German idealism and the Scottish and French enlightenments, and then from the birth of sociology in the nineteenth century through the twentieth century. While focusing on social thought, the book draws on many disciplines, including philosophy, anthropology, and political science. It demonstrate the profound difficulties most social thinkers—including liberals, socialists, and those intellectuals who could be regarded as the first sociologists—had in coming to terms with the phenomenon of war, the most obvious form of large-scale social violence. With only a few exceptions, these thinkers, who believed deeply in social progress, were unable to account for war because they regarded it as marginal or archaic, and on the verge of disappearing. This overly optimistic picture of the modern world persisted in social theory even in the twentieth century, as most sociologists and social theorists either ignored war and violence in their theoretical work or tried to explain it away. The failure of the social sciences and especially sociology to understand war, the book argues, must be seen as one of the greatest weaknesses of disciplines that claim to give a convincing diagnosis of our times.

The politics of welfare

2021 ◽  
pp. 147488512110080
Author(s):  
Lois McNay
Keyword(s):  
Social Policy ◽  
Social Conditions ◽  
Radical Politics ◽  
Contemporary World ◽  
Welfare Institutions ◽  
The Social ◽  
Original Argument ◽  
Collective Activism ◽  
Historical Model ◽  
Valuable Role

Steven Klein’s excellent new book The Work of Politics is an innovative, insightful and original argument about the valuable role that welfare institutions may play in democratic movements for change. In place of a one-sided Weberian view of welfare institutions as bureaucratic instruments of social control, Klein recasts them in Arendtian terms as ‘worldly mediators’ or participatory mechanisms that act as channels for a radical politics of democratic world making. Although Klein is careful to modulate this utopian vision through a developed account of power and domination, I question the relevance of this largely historical model of world-building activism for the contemporary world of welfare. I point to the way that decades of neoliberal social policy have arguably eroded many of the social conditions and relations of solidarity that are vital prerequisites for collective activism around welfare.

scholarly journals Correction: Accuracy of the FMF Bayes theorem-based model for predicting preeclampsia at 11–13 weeks of gestation in a Japanese population

2021 ◽  
Author(s):  
Minako Goto ◽  
Keiko Koide ◽  
Mayumi Tokunaka ◽  
Hiroko Takita ◽  
Shoko Hamada ◽  
...  
Keyword(s):  
Japanese Population ◽  
Bayes Theorem

scholarly journals Bayes Theorem and Protopathic Bias: Methodological Concerns When Addressing the Impact of Fetal Heart Rate Patterns on the Cesarean Section Rate

2020 ◽  
Vol 10 (03) ◽  
pp. e342-e345
Author(s):  
Jacques Balayla ◽  
Ariane Lasry ◽  
Yaron Gil ◽  
Alexander Volodarsky-Perel
Keyword(s):  
Heart Rate ◽  
Caesarean Section ◽  
Fetal Heart Rate ◽  
Predictive Power ◽  
Fetal Heart ◽  
Caesarean Section Rate ◽  
Bayes Theorem ◽  
The Poor ◽  
Clinical Scenarios ◽  
The Impact

AbstractOver the last 30 years, the caesarean section rate has reached global epidemic proportions. This trend is driven by multiple factors, an important one of which is the use and inconsistent interpretation of the electronic fetal monitoring (EFM) system. Despite its introduction in the 1960s, the EFM has not definitively improved neonatal outcomes, yet it has since significantly contributed to a seven-fold increase in the caesarean section rate. As we attempt to reduce the caesarean rates in the developed world, we should consider focusing on areas that have garnered little attention in the literature, such as physician sensitization to the poor predictive power of the EFM and the research method biases that are involved in studying the abnormal heart rate patterns—umbilical cord pH relationship. Herein, we apply Bayes theorem to different clinical scenarios to illustrate the poor predictive power of the EFM, as well as shed light on the principle of protopathic bias, which affects the classification of research outcomes among studies addressing the effects of the EFM on caesarean rates. We propose and discuss potential solutions to the aforementioned considerations, which include the re-examination of guidelines with which we interpret fetal heart rate patterns and the development of noninvasive technologies that evaluate fetal pH in real time.

scholarly journals Formulating the history matching problem with consistent error statistics

2021 ◽  
Author(s):  
Geir Evensen
Keyword(s):  
Simulation Model ◽  
Measurement Errors ◽  
History Matching ◽  
Critical Role ◽  
Bayes Theorem ◽  
Conditional Probability Density ◽  
Model Parameters ◽  
Rate Data ◽  
Matching Problem ◽  
Reservoir Prediction

AbstractIt is common to formulate the history-matching problem using Bayes’ theorem. From Bayes’, the conditional probability density function (pdf) of the uncertain model parameters is proportional to the prior pdf of the model parameters, multiplied by the likelihood of the measurements. The static model parameters are random variables characterizing the reservoir model while the observations include, e.g., historical rates of oil, gas, and water produced from the wells. The reservoir prediction model is assumed perfect, and there are no errors besides those in the static parameters. However, this formulation is flawed. The historical rate data only approximately represent the real production of the reservoir and contain errors. History-matching methods usually take these errors into account in the conditioning but neglect them when forcing the simulation model by the observed rates during the historical integration. Thus, the model prediction depends on some of the same data used in the conditioning. The paper presents a formulation of Bayes’ theorem that considers the data dependency of the simulation model. In the new formulation, one must update both the poorly known model parameters and the rate-data errors. The result is an improved posterior ensemble of prediction models that better cover the observations with more substantial and realistic uncertainty. The implementation accounts correctly for correlated measurement errors and demonstrates the critical role of these correlations in reducing the update’s magnitude. The paper also shows the consistency of the subspace inversion scheme by Evensen (Ocean Dyn. 54, 539–560 2004) in the case with correlated measurement errors and demonstrates its accuracy when using a “larger” ensemble of perturbations to represent the measurement error covariance matrix.

There Is No Unity, Only Politics: A Reply to Kurtz

2020 ◽  
pp. 216747952098188
Author(s):  
Michael L. Butterworth
Keyword(s):  
Social Justice ◽  
Political Change ◽  
Social Differences ◽  
Original Argument

Jeff Kurtz offers a substantive response to my essay, “Sport and the Quest for Unity.” Although he takes seriously my claims that “unity” is too often used within sports as a rhetorical means for eliding important cultural, political, and social differences, he also responds by suggesting that I tacitly endorse claims to unity when made on behalf of social justice causes. Moreover, he contends that the unity modeled by social justice advocates is “suffocating” and thus stifles legitimate differences among and between those who would seek political change. I reply in this essay by clarifying what I think is a misreading of my original argument. More importantly, I point to potential consequences of Kurtz’s argument, which I maintain over-reads the degree to which unity has been performed and implies a false equivalency between institutional forms of power and those making the case of justice.

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