Scientific Inference

Author: Harold Jeffreys

Publisher: Cambridge University Press

ISBN: 0521084466

Category: Science

Page: 273

View: 8248

Logic and scientific inference; Probability; Sampling; Errors; Physical magnitudes; Mensuration; Newtonian dynamics; Light and relativity; Miscellaneous questions; Statistical mechanics and quantum theory.

Scientific Inference

Author: Harold Jeffreys

Publisher: Read Books Ltd

ISBN: 1447494784

Category: Science

Page: 260

View: 4050

Originally published in 1931. The present work had its beginnings in a series of papers published jointly some years ago by Dr Dorothy Wrinch and myself. Both before and since that time several books purporting to give analyses of the principles of scientific inquiry have appeared, but it seems to me that none of them gives adequate attention to the chief guiding principle of both scientific and everyday knowledge that it is possible to learn from experience and to make inferences from it beyond the data directly known by sensation. Discussions from the philosophical and logical point of view have tended to the conclusion that this principle cannot be justified by logic alone, which is true, and have left it at that. In discussions by physicists, on the other hand, it hardly seems to be noticed that such a principle exists. In the present work the principle is frankly adopted as a primitive postulate and its consequences are developed. It is found to lead to an explanation and a justification of the high probabilities attached in practice to simple quantitative laws, and thereby to a recasting of the processes involved in description. As illustrations of the actual relations of scientific laws to experience it is shown how the sciences of mensuration and dynamics may be developed. I have been stimulated to an interest in the subject myself on account of the fact that in my work in the subjects of cosmogony and geophysics it has habitually been necessary to apply physical laws far beyond their original range of verification in both time and distance, and the problems involved in such extrapolation have therefore always been prominent. This is a high quality digital version of the original title, thus a few of the images may be slightly blurred and difficult to read.

Paradoxes in Scientific Inference

Author: Mark Chang

Publisher: CRC Press

ISBN: 1466509872

Category: Computers

Page: 291

View: 5595

Paradoxes are poems of science and philosophy that collectively allow us to address broad multidisciplinary issues within a microcosm. A true paradox is a source of creativity and a concise expression that delivers a profound idea and provokes a wild and endless imagination. The study of paradoxes leads to ultimate clarity and, at the same time, indisputably challenges your mind. Paradoxes in Scientific Inference analyzes paradoxes from many different perspectives: statistics, mathematics, philosophy, science, artificial intelligence, and more. The book elaborates on findings and reaches new and exciting conclusions. It challenges your knowledge, intuition, and conventional wisdom, compelling you to adjust your way of thinking. Ultimately, you will learn effective scientific inference through studying the paradoxes.

The Foundations of Scientific Inference

Author: Wesley Salmon

Publisher: University of Pittsburgh Pre

ISBN: 0822971259

Category: Philosophy

Page: 168

View: 8897

Not since Ernest Nagel’s 1939 monograph on the theory of probability has there been a comprehensive elementary survey of the philosophical problems of probablity and induction. This is an authoritative and up-to-date treatment of the subject, and yet it is relatively brief and nontechnical. Hume’s skeptical arguments regarding the justification of induction are taken as a point of departure, and a variety of traditional and contemporary ways of dealing with this problem are considered. The author then sets forth his own criteria of adequacy for interpretations of probability. Utilizing these criteria he analyzes contemporary theories of probability, as well as the older classical and subjective interpretations.

Scientific Inference

Learning from Data

Author: Simon Vaughan

Publisher: Cambridge University Press

ISBN: 1107434211

Category: Science

Page: 312

View: 2387

Providing the knowledge and practical experience to begin analysing scientific data, this book is ideal for physical sciences students wishing to improve their data handling skills. The book focuses on explaining and developing the practice and understanding of basic statistical analysis, concentrating on a few core ideas, such as the visual display of information, modelling using the likelihood function, and simulating random data. Key concepts are developed through a combination of graphical explanations, worked examples, example computer code and case studies using real data. Students will develop an understanding of the ideas behind statistical methods and gain experience in applying them in practice. Further resources are available at, including data files for the case studies so students can practise analysing data, and exercises to test students' understanding.

Phantom Risk

Scientific Inference and the Law

Author: Kenneth R. Foster,David E. Bernstein,Peter W. Huber

Publisher: MIT Press

ISBN: 9780262561198

Category: Law

Page: 457

View: 801

Phantom risks are risks whose very existence is unproven and perhaps unprovable, yet they raise real problems at the interface of science and the law. Phantom Risk surveys a dozen scientific issues that have led to public controversy and litigation - among them, miscarriage from the use of video display terminals, birth defects in children whose mothers used the drug Bendectin, and cancer from low-intensity magnetic fields, and from airborne asbestos. It presents the scientific evidence behind these and other issues and summarizes the resulting litigation.Focusing on the great disparity between the scientific evidence that is sufficient to arouse public fears and that needed to establish a hazard or its absence, these original contributions probe the problem of scientific ambiguity in risk assessment, and the mayhem this creates in the courtroom.Although the authors are clearly optimistic about the use of science to detect and evaluate risks, they recognize the difficulty of inferring cause-and-effect relationships from epidemiological (observational) evidence and of inferring risks to humans from high-dose animal experiments, the two major sources of evidence. The final chapter reviews the exceptionally difficult problem of how the legal impact of disputes about phantom risks can be reduced.Kenneth R. Foster is Associate Professor in the Department of Bioengineering at the University of Pennsylvania. David E. Bernstein is an attorney at the law firm of Crowell & Moring. Peter W. Huber is a Senior Fellow of the Manhattan Institute for Policy Research and serves as Counsel to the law firm of Mayer, Brown & Platt.

The Foundations of Scientific Inference

50th Anniversary Edition

Author: Wesley C. Salmon

Publisher: University of Pittsburgh Press

ISBN: 0822982943

Category: Science

Page: 208

View: 5433

After its publication in 1967, The Foundations of Scientific Inference taught a generation of students and researchers about the problem of induction, the interpretation of probability, and confirmation theory. Fifty years later, Wesley C. Salmon’s book remains one of the clearest introductions to these fundamental problems in the philosophy of science. With The Foundations of Scientific Inference, Salmon presented a coherent vision of the nature of scientific reasoning, explored the philosophical underpinnings of scientific investigation, and introduced readers to key movements in epistemology and to leading philosophers of the twentieth century—such as Karl Popper, Rudolf Carnap, and Hans Reichenbach—offering a critical assessment and developing his own distinctive views on topics that are still of central importance today. This anniversary edition of Salmon’s foundational work in the philosophy of science features a detailed introduction by Christopher Hitchcock, which examines the book’s origins, influences, and major themes, its impact and enduring effects, the disputes it raised, and its place in current studies, revisiting Salmon’s ideas for a new audience of philosophers, historians, scientists, and students.

Scientific Inference, Data Analysis, and Robustness

Proceedings of a Conference Conducted by the Mathematics Research Center, the University of Wisconsin—Madison, November 4–6, 1981

Author: G. E. P. Box,Tom Leonard,Chien-Fu Wu

Publisher: Academic Press

ISBN: 1483259390

Category: Mathematics

Page: 316

View: 3064

Mathematics Research Center Symposium: Scientific Inference, Data Analysis, and Robustness focuses on the philosophy of statistical modeling, including model robust inference and analysis of data sets. The selection first elaborates on pivotal inference and the conditional view of robustness and some philosophies of inference and modeling, including ideas on modeling, significance testing, and scientific discovery. The book then ponders on parametric empirical Bayes confidence intervals, ecumenism in statistics, and frequency properties of Bayes rules. Discussions focus on consistency of Bayes rules, scientific method and the human brain, and statistical estimation and criticism. The book takes a look at the purposes and limitations of data analysis, likelihood, shape, and adaptive inference, statistical inference and measurement of entropy, and the robustness of a hierarchical model for multinomials and contingency tables. Topics include numerical results for contingency tables and robustness, multinomials, flattening constants, and mixed Dirichlet priors, entropy and likelihood, and test as measurement of entropy. The selection is a valuable reference for researchers interested in robust inference and analysis of data sets.

Designing Social Inquiry

Scientific Inference in Qualitative Research

Author: Gary King,Robert O. Keohane,Sidney Verba

Publisher: Princeton University Press

ISBN: 9781400821211

Category: Social Science

Page: 264

View: 7231

While heated arguments between practitioners of qualitative and quantitative research have begun to test the very integrity of the social sciences, Gary King, Robert Keohane, and Sidney Verba have produced a farsighted and timely book that promises to sharpen and strengthen a wide range of research performed in this field. These leading scholars, each representing diverse academic traditions, have developed a unified approach to valid descriptive and causal inference in qualitative research, where numerical measurement is either impossible or undesirable. Their book demonstrates that the same logic of inference underlies both good quantitative and good qualitative research designs, and their approach applies equally to each. Providing precepts intended to stimulate and discipline thought, the authors explore issues related to framing research questions, measuring the accuracy of data and uncertainty of empirical inferences, discovering causal effects, and generally improving qualitative research. Among the specific topics they address are interpretation and inference, comparative case studies, constructing causal theories, dependent and explanatory variables, the limits of random selection, selection bias, and errors in measurement. Mathematical notation is occasionally used to clarify concepts, but no prior knowledge of mathematics or statistics is assumed. The unified logic of inference that this book explicates will be enormously useful to qualitative researchers of all traditions and substantive fields.

Refining the Concept of Scientific Inference When Working with Big Data

Proceedings of a Workshop

Author: National Academies of Sciences, Engineering, and Medicine,Division on Engineering and Physical Sciences,Board on Mathematical Sciences and Their Applications,Committee on Applied and Theoretical Statistics

Publisher: National Academies Press

ISBN: 0309454476

Category: Mathematics

Page: 114

View: 4487

The concept of utilizing big data to enable scientific discovery has generated tremendous excitement and investment from both private and public sectors over the past decade, and expectations continue to grow. Using big data analytics to identify complex patterns hidden inside volumes of data that have never been combined could accelerate the rate of scientific discovery and lead to the development of beneficial technologies and products. However, producing actionable scientific knowledge from such large, complex data sets requires statistical models that produce reliable inferences (NRC, 2013). Without careful consideration of the suitability of both available data and the statistical models applied, analysis of big data may result in misleading correlations and false discoveries, which can potentially undermine confidence in scientific research if the results are not reproducible. In June 2016 the National Academies of Sciences, Engineering, and Medicine convened a workshop to examine critical challenges and opportunities in performing scientific inference reliably when working with big data. Participants explored new methodologic developments that hold significant promise and potential research program areas for the future. This publication summarizes the presentations and discussions from the workshop.

Foundations of Inference in Natural Science

Author: J O Wisdom

Publisher: Routledge

ISBN: 1135027862

Category: Philosophy

Page: 242

View: 5039

Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction and Part IV outlines the shape of this problem and its solution take if transformed by the present approach.

On Science, Inference, Information and Decision-Making

Selected Essays in the Philosophy of Science

Author: A. Szaniawski

Publisher: Springer Science & Business Media

ISBN: 9401152608

Category: Philosophy

Page: 242

View: 2716

There are two competing pictures of science. One considers science as a system of inferences, whereas another looks at science as a system of actions. The essays included in this collection offer a view which intends to combine both pictures. This compromise is well illustrated by Szaniawski's analysis of statistical inferences. It is shown that traditional approaches to the foundations of statistics do not need to be regarded as conflicting with each other. Thus, statistical rules can be treated as rules of behaviour as well as rules of inference. Szaniawski's uniform approach relies on the concept of rationality, analyzed from the point of view of decision theory. Applications of formal tools to the problem of justice and division of goods shows that the concept of rationality has a wider significance. Audience: The book will be of interest to philosophers of science, logicians, ethicists and mathematicians.

Statistical Methods, Experimental Design, and Scientific Inference

Author: R. A. Fisher

Publisher: OUP Oxford

ISBN: 9780198522294

Category: Mathematics

Page: 832

View: 666

The writings of R.A. Fisher have proved to be as relevant today as when they were written. This book brings together as a single volume three of his most influential textbooks: Statistical Methods for Research Workers, Statistical Methods and Scientific Inference, and The Design of Experiments. In a new Foreword, written for this edition, Professor Frank Yates discusses some of the key issues tackled in the textbooks, and how they relate to modern statistical practice.