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| jaynes 2003 probability theory the logic of science: Probability Theory , 2013 Probability theory |
| jaynes 2003 probability theory the logic of science: E.T. Jaynes Edwin T. Jaynes, 1989-04-30 The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le. , as distributions that are most non-committal with regard to missing information among all those satisfying the macroscopically given constraints). There is then no need to make additional assumptions of ergodicity or metric transitivity; the theory proceeds entirely by inference from macroscopic measurements and the underlying dynamical assumptions. Moreover, the method of maximizing the entropy is completely general and applies, in particular, to irreversible processes as well as to reversible ones. The next three chapters provide a broader framework - at once Bayesian and objective - for maximum entropy inference. The basic principles of inference, including the usual axioms of probability, are seen to rest on nothing more than requirements of consistency, above all, the requirement that in two problems where we have the same information we must assign the same probabilities. Thus, statistical mechanics is viewed as a branch of a general theory of inference, and the latter as an extension of the ordinary logic of consistency. Those who are familiar with the literature of statistics and statistical mechanics will recognize in both of these steps a genuine 'scientific revolution' - a complete reversal of earlier conceptions - and one of no small significance. |
| jaynes 2003 probability theory the logic of science: Bayesian Statistics the Fun Way Will Kurt, 2019-07-09 Fun guide to learning Bayesian statistics and probability through unusual and illustrative examples. Probability and statistics are increasingly important in a huge range of professions. But many people use data in ways they don't even understand, meaning they aren't getting the most from it. Bayesian Statistics the Fun Way will change that. This book will give you a complete understanding of Bayesian statistics through simple explanations and un-boring examples. Find out the probability of UFOs landing in your garden, how likely Han Solo is to survive a flight through an asteroid shower, how to win an argument about conspiracy theories, and whether a burglary really was a burglary, to name a few examples. By using these off-the-beaten-track examples, the author actually makes learning statistics fun. And you'll learn real skills, like how to: - How to measure your own level of uncertainty in a conclusion or belief - Calculate Bayes theorem and understand what it's useful for - Find the posterior, likelihood, and prior to check the accuracy of your conclusions - Calculate distributions to see the range of your data - Compare hypotheses and draw reliable conclusions from them Next time you find yourself with a sheaf of survey results and no idea what to do with them, turn to Bayesian Statistics the Fun Way to get the most value from your data. |
| jaynes 2003 probability theory the logic of science: Tychomancy Michael Strevens, 2013-06-01 Michael Strevens makes three claims about rules for inferring physical probability. They are reliable. They constitute a key part of the physical intuition that allows us to navigate the world safely in the absence of scientific knowledge. And they played a crucial role in scientific innovation, from statistical physics to natural selection. |
| jaynes 2003 probability theory the logic of science: Introduction to Probability Charles Miller Grinstead, James Laurie Snell, 2012-10-30 This text is designed for an introductory probability course at the university level for sophomores, juniors, and seniors in mathematics, physical and social sciences, engineering, and computer science. It presents a thorough treatment of ideas and techniques necessary for a firm understanding of the subject. |
| jaynes 2003 probability theory the logic of science: Bernoulli's Fallacy Aubrey Clayton, 2021-08-03 There is a logical flaw in the statistical methods used across experimental science. This fault is not a minor academic quibble: it underlies a reproducibility crisis now threatening entire disciplines. In an increasingly statistics-reliant society, this same deeply rooted error shapes decisions in medicine, law, and public policy with profound consequences. The foundation of the problem is a misunderstanding of probability and its role in making inferences from observations. Aubrey Clayton traces the history of how statistics went astray, beginning with the groundbreaking work of the seventeenth-century mathematician Jacob Bernoulli and winding through gambling, astronomy, and genetics. Clayton recounts the feuds among rival schools of statistics, exploring the surprisingly human problems that gave rise to the discipline and the all-too-human shortcomings that derailed it. He highlights how influential nineteenth- and twentieth-century figures developed a statistical methodology they claimed was purely objective in order to silence critics of their political agendas, including eugenics. Clayton provides a clear account of the mathematics and logic of probability, conveying complex concepts accessibly for readers interested in the statistical methods that frame our understanding of the world. He contends that we need to take a Bayesian approach—that is, to incorporate prior knowledge when reasoning with incomplete information—in order to resolve the crisis. Ranging across math, philosophy, and culture, Bernoulli’s Fallacy explains why something has gone wrong with how we use data—and how to fix it. |
| jaynes 2003 probability theory the logic of science: Bayesian Data Analysis, Third Edition Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, Donald B. Rubin, 2013-11-01 Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page. |
| jaynes 2003 probability theory the logic of science: Philosophical Lectures on Probability Bruno de Finetti, 2008-05-20 Bruno de Finetti (1906–1985) is the founder of the subjective interpretation of probability, together with the British philosopher Frank Plumpton Ramsey. His related notion of “exchangeability” revolutionized the statistical methodology. This book (based on a course held in 1979) explains in a language accessible also to non-mathematicians the fundamental tenets and implications of subjectivism, according to which the probability of any well specified fact F refers to the degree of belief actually held by someone, on the ground of her whole knowledge, on the truth of the assertion that F obtains. |
| jaynes 2003 probability theory the logic of science: Physics and Probability Edwin T. Jaynes, Walter T. Grandy, P. W. Milonni, 1993-09-02 A collection of papers on the pioneering work of Edwin T. Jaynes in statistical physics, quantum optics and probability theory. |
| jaynes 2003 probability theory the logic of science: Bayesian Logical Data Analysis for the Physical Sciences Phil Gregory, 2005-04-14 Bayesian inference provides a simple and unified approach to data analysis, allowing experimenters to assign probabilities to competing hypotheses of interest, on the basis of the current state of knowledge. By incorporating relevant prior information, it can sometimes improve model parameter estimates by many orders of magnitude. This book provides a clear exposition of the underlying concepts with many worked examples and problem sets. It also discusses implementation, including an introduction to Markov chain Monte-Carlo integration and linear and nonlinear model fitting. Particularly extensive coverage of spectral analysis (detecting and measuring periodic signals) includes a self-contained introduction to Fourier and discrete Fourier methods. There is a chapter devoted to Bayesian inference with Poisson sampling, and three chapters on frequentist methods help to bridge the gap between the frequentist and Bayesian approaches. Supporting Mathematica® notebooks with solutions to selected problems, additional worked examples, and a Mathematica tutorial are available at www.cambridge.org/9780521150125. |
| jaynes 2003 probability theory the logic of science: First Look At Rigorous Probability Theory, A (2nd Edition) Jeffrey S Rosenthal, 2006-11-14 This textbook is an introduction to probability theory using measure theory. It is designed for graduate students in a variety of fields (mathematics, statistics, economics, management, finance, computer science, and engineering) who require a working knowledge of probability theory that is mathematically precise, but without excessive technicalities. The text provides complete proofs of all the essential introductory results. Nevertheless, the treatment is focused and accessible, with the measure theory and mathematical details presented in terms of intuitive probabilistic concepts, rather than as separate, imposing subjects. In this new edition, many exercises and small additional topics have been added and existing ones expanded. The text strikes an appropriate balance, rigorously developing probability theory while avoiding unnecessary detail. |
| jaynes 2003 probability theory the logic of science: Bayesian Spectrum Analysis and Parameter Estimation G. Larry Bretthorst, 2013-03-09 This work is essentially an extensive revision of my Ph.D. dissertation, [1J. It 1S primarily a research document on the application of probability theory to the parameter estimation problem. The people who will be interested in this material are physicists, economists, and engineers who have to deal with data on a daily basis; consequently, we have included a great deal of introductory and tutorial material. Any person with the equivalent of the mathematics background required for the graduate level study of physics should be able to follow the material contained in this book, though not without eIfort. From the time the dissertation was written until now (approximately one year) our understanding of the parameter estimation problem has changed extensively. We have tried to incorporate what we have learned into this book. I am indebted to a number of people who have aided me in preparing this docu ment: Dr. C. Ray Smith, Steve Finney, Juana Sunchez, Matthew Self, and Dr. Pat Gibbons who acted as readers and editors. In addition, I must extend my deepest thanks to Dr. Joseph Ackerman for his support during the time this manuscript was being prepared. |
| jaynes 2003 probability theory the logic of science: The Origin of Consciousness in the Breakdown of the Bicameral Mind Julian Jaynes, 2000-08-15 National Book Award Finalist: “This man’s ideas may be the most influential, not to say controversial, of the second half of the twentieth century.”—Columbus Dispatch At the heart of this classic, seminal book is Julian Jaynes's still-controversial thesis that human consciousness did not begin far back in animal evolution but instead is a learned process that came about only three thousand years ago and is still developing. The implications of this revolutionary scientific paradigm extend into virtually every aspect of our psychology, our history and culture, our religion—and indeed our future. “Don’t be put off by the academic title of Julian Jaynes’s The Origin of Consciousness in the Breakdown of the Bicameral Mind. Its prose is always lucid and often lyrical…he unfolds his case with the utmost intellectual rigor.”—The New York Times “When Julian Jaynes . . . speculates that until late in the twentieth millennium BC men had no consciousness but were automatically obeying the voices of the gods, we are astounded but compelled to follow this remarkable thesis.”—John Updike, The New Yorker “He is as startling as Freud was in The Interpretation of Dreams, and Jaynes is equally as adept at forcing a new view of known human behavior.”—American Journal of Psychiatry |
| jaynes 2003 probability theory the logic of science: Data Analysis Devinderjit Sivia, John Skilling, 2006-06-02 One of the strengths of this book is the author's ability to motivate the use of Bayesian methods through simple yet effective examples. - Katie St. Clair MAA Reviews. |
| jaynes 2003 probability theory the logic of science: Stochasticity in Processes Peter Schuster, 2016-10-14 This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part. Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed to produce artifacts in interpretation unless the observer has a solid background in the mathematics of limited reproducibility. The material covered is presented in a modular approach, allowing more advanced sections to be skipped if the reader is primarily interested in applications. At the same time, most derivations of analytical solutions for the selected examples are provided in full length to guide more advanced readers in their attempts to derive solutions on their own. The book employs uniform notation throughout, and a glossary has been added to define the most important notions discussed. |
| jaynes 2003 probability theory the logic of science: Princeton Companion to Applied Mathematics Nicholas J. Higham, Mark R. Dennis, Paul Glendinning, Paul A. Martin, Fadil Santosa, Jared Tanner, 2015-09-09 The must-have compendium on applied mathematics This is the most authoritative and accessible single-volume reference book on applied mathematics. Featuring numerous entries by leading experts and organized thematically, it introduces readers to applied mathematics and its uses; explains key concepts; describes important equations, laws, and functions; looks at exciting areas of research; covers modeling and simulation; explores areas of application; and more. Modeled on the popular Princeton Companion to Mathematics, this volume is an indispensable resource for undergraduate and graduate students, researchers, and practitioners in other disciplines seeking a user-friendly reference book on applied mathematics. Features nearly 200 entries organized thematically and written by an international team of distinguished contributors Presents the major ideas and branches of applied mathematics in a clear and accessible way Explains important mathematical concepts, methods, equations, and applications Introduces the language of applied mathematics and the goals of applied mathematical research Gives a wide range of examples of mathematical modeling Covers continuum mechanics, dynamical systems, numerical analysis, discrete and combinatorial mathematics, mathematical physics, and much more Explores the connections between applied mathematics and other disciplines Includes suggestions for further reading, cross-references, and a comprehensive index |
| jaynes 2003 probability theory the logic of science: Probability and Social Science Daniel Courgeau, 2012-02-22 This work examines in depth the methodological relationships that probability and statistics have maintained with the social sciences from their emergence. It covers both the history of thought and current methods. First it examines in detail the history of the different paradigms and axioms for probability, from their emergence in the seventeenth century up to the most recent developments of the three major concepts: objective, subjective and logicist probability. It shows the statistical inference they permit, different applications to social sciences and the main problems they encounter. On the other side, from social sciences—particularly population sciences—to probability, it shows the different uses they made of probabilistic concepts during their history, from the seventeenth century, according to their paradigms: cross-sectional, longitudinal, hierarchical, contextual and multilevel approaches. While the ties may have seemed loose at times, they have more often been very close: some advances in probability were driven by the search for answers to questions raised by the social sciences; conversely, the latter have made progress thanks to advances in probability. This dual approach sheds new light on the historical development of the social sciences and probability, and on the enduring relevance of their links. It permits also to solve a number of methodological problems encountered all along their history. |
| jaynes 2003 probability theory the logic of science: Bayesian Rationality Mike Oaksford, Nick Chater, 2007-02-22 For almost 2,500 years, the Western concept of what is to be human has been dominated by the idea that the mind is the seat of reason - humans are, almost by definition, the rational animal. In this text a more radical suggestion for explaining these puzzling aspects of human reasoning is put forward. |
| jaynes 2003 probability theory the logic of science: Advanced Lectures on Machine Learning Olivier Bousquet, Ulrike von Luxburg, Gunnar Rätsch, 2004-09-02 Machine Learning has become a key enabling technology for many engineering applications, investigating scientific questions and theoretical problems alike. To stimulate discussions and to disseminate new results, a summer school series was started in February 2002, the documentation of which is published as LNAI 2600. This book presents revised lectures of two subsequent summer schools held in 2003 in Canberra, Australia, and in Tübingen, Germany. The tutorial lectures included are devoted to statistical learning theory, unsupervised learning, Bayesian inference, and applications in pattern recognition; they provide in-depth overviews of exciting new developments and contain a large number of references. Graduate students, lecturers, researchers and professionals alike will find this book a useful resource in learning and teaching machine learning. |
| jaynes 2003 probability theory the logic of science: Elements of Logic as a Science of Propositions Emily Elizabeth Constance 184 Jones, 2023-07-18 In this groundbreaking work, Emily Elizabeth Constance Jones provides a detailed introduction to the field of logic, focusing in particular on the science of propositions. Jones's clear and concise writing style make this work accessible to readers from all backgrounds, and it remains a popular textbook on logic to this day. 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 (individual or corporate) 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. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. |
| jaynes 2003 probability theory the logic of science: Bayesian Philosophy of Science Jan Sprenger, Stephan Hartmann, 2019-08-23 How should we reason in science? Jan Sprenger and Stephan Hartmann offer a refreshing take on classical topics in philosophy of science, using a single key concept to explain and to elucidate manifold aspects of scientific reasoning. They present good arguments and good inferences as being characterized by their effect on our rational degrees of belief. Refuting the view that there is no place for subjective attitudes in 'objective science', Sprenger and Hartmann explain the value of convincing evidence in terms of a cycle of variations on the theme of representing rational degrees of belief by means of subjective probabilities (and changing them by Bayesian conditionalization). In doing so, they integrate Bayesian inference--the leading theory of rationality in social science--with the practice of 21st century science. Bayesian Philosophy of Science thereby shows how modeling such attitudes improves our understanding of causes, explanations, confirming evidence, and scientific models in general. It combines a scientifically minded and mathematically sophisticated approach with conceptual analysis and attention to methodological problems of modern science, especially in statistical inference, and is therefore a valuable resource for philosophers and scientific practitioners. |
| jaynes 2003 probability theory the logic of science: Probability David J. Morin, 2016 Preface -- Combinatorics -- Probability -- Expectation values -- Distributions -- Gaussian approximations -- Correlation and regression -- Appendices. |
| jaynes 2003 probability theory the logic of science: Bayesian Reasoning In Data Analysis: A Critical Introduction Giulio D'agostini, 2003-06-13 This book provides a multi-level introduction to Bayesian reasoning (as opposed to “conventional statistics”) and its applications to data analysis. The basic ideas of this “new” approach to the quantification of uncertainty are presented using examples from research and everyday life. Applications covered include: parametric inference; combination of results; treatment of uncertainty due to systematic errors and background; comparison of hypotheses; unfolding of experimental distributions; upper/lower bounds in frontier-type measurements. Approximate methods for routine use are derived and are shown often to coincide — under well-defined assumptions! — with “standard” methods, which can therefore be seen as special cases of the more general Bayesian methods. In dealing with uncertainty in measurements, modern metrological ideas are utilized, including the ISO classification of uncertainty into type A and type B. These are shown to fit well into the Bayesian framework. |
| jaynes 2003 probability theory the logic of science: The Dialogical Roots of Deduction Catarina Dutilh Novaes, 2020-12-17 The first comprehensive account of the concept and practices of deduction covering philosophy, history, cognition and mathematical practice. |
| jaynes 2003 probability theory the logic of science: In Defence of Objective Bayesianism Jon Williamson, 2010-05-13 Objective Bayesianism is a methodological theory that is currently applied in statistics, philosophy, artificial intelligence, physics and other sciences. This book develops the formal and philosophical foundations of the theory, at a level accessible to a graduate student with some familiarity with mathematical notation. |
| jaynes 2003 probability theory the logic of science: Bayesian Probability Theory Wolfgang von der Linden, Volker Dose, Udo von Toussaint, 2014-06-12 Covering all aspects of probability theory, statistics and data analysis from a Bayesian perspective for graduate students and researchers. |
| jaynes 2003 probability theory the logic of science: Analogies Between Analogies S. M. Ulam, 2022-03-25 During his forty-year association with the Los Alamos National Laboratory, mathematician Stanislaw Ulam wrote many Laboratory Reports, usually in collaboration with colleagues. Some of them remain classified to this day. The rest are gathered in this volume and for the first time are easily accesible to mathematicians, physical scientists, and historians. The timeliness of these papers is remarkable. They contain seminal ideas in such fields as nonlinear stochastic processes, parallel computation, cellular automata, and mathematical biology. The collection is of historical interest as well, During and after World War II, the complexity of problems at the frontiers of science surpassed any technology that had ever existed. Electronic computing machines had to be developed and new computing methods had to be invented based on the most abstract ideas from the foundations of mathematics and theoretical physics. To these problems and others in physics, astronomy, and biology, Ulam was able to bring both general insights and specific conceptual contributions. His fertile ideas were far ahead of their time, and ranged over many branches of science. In fact, his mathematical versatility fulfilled the statement of his friend and mentor, the great Polish mathematician Stefan Banach, who claimed that the very best mathematicians see analogies between analogies. Introduced by A. R. Bednarek and Francoise Ulam, these Los Alamos reports represent a unique view of one of the twentieth century's intellectual masters and scientific pioneers. This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1990. |
| jaynes 2003 probability theory the logic of science: The Fundamentals of Risk Measurement Christopher Marrison, 2002-07-18 A step-by-step guidebook for understanding—and implementing—integrated financial risk measurement and management The Fundamentals of Risk Measurement introduces the state-of-the-art tools and practices necessary for planning, executing, and maintaining risk management in today’s volatile financial environment. This comprehensive book provides description and analysis of topics including: Economic capital Risk adjusted return on capital (RAROC) Shareholder Value Added (SVA) Value at Risk (VaR) Asset/liability management (ALM) Credit risk for a single facility Credit risk for portfolios Operating risk Inter-risk diversification The Basel Committee Capital Accords The banking world is driven by risk. The Fundamentals of Risk Measurement shows you how to quantify that risk, outlining an integrated framework for risk measurement and management that is straightforward, practical for implementation, and based on the realities of today’s tumultuous global marketplace. “Banks make money in one of two ways: providing services to customers and taking risks. In this book, we address the business of making money by taking risk....”—From the Introduction In The Fundamentals of Risk Measurement, financial industry veteran Chris Marrison examines what banks must do to succeed in the business of making money by taking risk. Encompassing the three primary areas of banking risk—market, credit, and operational—and doing so in a uniquely intuitive, step-by-step format, Marrison provides hands-on details on the primary tools for financial risk measurement and management, including: Plain-English evaluation of specific risk measurement tools and techniques Use of Value at Risk (VaR) for assessment of market risk for trading operations Asset/liability management (ALM) techniques, transfer pricing, and managing market and liquidity risk The many available methods for analyzing portfolios of credit risks Using RAROC to compare the risk-adjusted profitability of businesses and price transactions In addition, woven throughout The Fundamentals of Risk Measurement are principles underlying the regulatory capital requirements of the Basel Committee on Banking Supervision, and what banks must do to understand and implement them. The requirements are defined, implications of the New Capital Accord are presented, and the major steps that a bank must take to implement the New Accord are discussed. The resulting thumbnail sketch of the Basel Committee, and specifically the New Capital Accord, is valuable as both a ready reference and a foundation for further study of this important initiative. Risk is unavoidable in the financial industry. It can, however, be measured and managed to provide the greatest risk-adjusted return, and limit the negative impacts of risk to a bank’s shareholders as well as potential borrowers and lenders. The Fundamentals of Risk Management provides risk managers with an approach to risk-taking that is both informed and prudent, one that shows operations managers how to control risk exposures as it allows decision-making executives to direct resources to opportunities that are expected to create maximum return with minimum risk. The result is today’s most complete introduction to the business of risk, and a valuable reference for anyone from the floor trader to the officer in charge of overseeing the entire risk management operation. |
| jaynes 2003 probability theory the logic of science: Complex Engineered Systems Dan Braha, Ali A. Minai, Yaneer Bar-Yam, 2007-06-24 Recent advances in science and technology have led to a rapid increase in the complexity of most engineered systems. In many notable cases, this change has been a qualitative one rather than merely one of magnitude. A new class of Complex Engineered Systems (CES) has emerged as a result of technologies such as the Internet, GPS, wireless networking, micro-robotics, MEMS, fiber-optics and nanotechnology. These complex engineered systems are composed of many heterogeneous subsystems and are characterized by observable complex behaviors that emerge as a result of nonlinear spatio-temporal interactions among the subsystems at several levels of organization and abstraction. Examples of such systems include the World-Wide Web, air and ground traffic networks, distributed manufacturing environments, and globally distributed supply networks, as well as new paradigms such as self-organizing sensor networks, self-configuring robots, swarms of autonomous aircraft, smart materials and structures, and self-organizing computers. Understanding, designing, building and controlling such complex systems is going to be a central challenge for engineers in the coming decades. |
| jaynes 2003 probability theory the logic of science: A Business Analyst's Introduction to Business Analytics Adam Fleischhacker, 2020-07-20 This up-to-date business analytics textbook (published in July 2020) will get you harnessing the power of the R programming language to: manipulate and model data, discover and communicate insight, to visually communicate that insight, and successfully advocate for change within an organization. Book Description A frequent teaching-award winning professor with an analytics-industry background shares his hands-on guide to learning business analytics. It is the first textbook addressing a complete and modern business analytics workflow that includes data manipulation, data visualization, modelling business problems with graphical models, translating graphical models into code, and presenting insights back to stakeholders. Book Highlights Content that is accessible to anyone, even most analytics beginners. If you have taken a stats course, you are good to go. Assumes no knowledge of the R programming language. Provides introduction to R, RStudio, and the Tidyverse. Provides a solid foundation and an implementable workflow for anyone wading into the Bayesian inference waters. Provides a complete workflow within the R-ecosystem; there is no need to learn several programming languages or work through clunky interfaces between software tools. First book introducing two powerful R-packages - `causact` for visual modelling of business problems and `greta` which is an R interface to `TensorFlow` used for Bayesian inference. Uses the intuitive coding practices of the `tidyverse` including using `dplyr` for data manipulation and `ggplot2` for data visualization. Datasets that are freely and easily accessible. Code for generating all results and almost every visualization used in the textbook. Do not learn statistical computation or fancy math in a vacuum, learn it through this guide within the context of solving business problems. |
| jaynes 2003 probability theory the logic of science: All of Statistics Larry Wasserman, 2004-09-17 This book is for people who want to learn probability and statistics quickly. It brings together many of the main ideas in modern statistics in one place. The book is suitable for students and researchers in statistics, computer science, data mining and machine learning. This book covers a much wider range of topics than a typical introductory text on mathematical statistics. It includes modern topics like nonparametric curve estimation, bootstrapping and classification, topics that are usually relegated to follow-up courses. The reader is assumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. The text can be used at the advanced undergraduate and graduate level. Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award and the 2002 winner of the Centre de recherches mathematiques de Montreal–Statistical Society of Canada Prize in Statistics. He is Associate Editor of The Journal of the American Statistical Association and The Annals of Statistics. He is a fellow of the American Statistical Association and of the Institute of Mathematical Statistics. |
| jaynes 2003 probability theory the logic of science: Ten Great Ideas about Chance Persi Diaconis, Frederick Brian Skyrms, 2017-11-07 A fascinating account of the breakthrough ideas that transformed probability and statistics In the sixteenth and seventeenth centuries, gamblers and mathematicians transformed the idea of chance from a mystery into the discipline of probability, setting the stage for a series of breakthroughs that enabled or transformed innumerable fields, from gambling, mathematics, statistics, economics, and finance to physics and computer science. This book tells the story of ten great ideas about chance and the thinkers who developed them, tracing the philosophical implications of these ideas as well as their mathematical impact. Persi Diaconis and Brian Skyrms begin with Gerolamo Cardano, a sixteenth-century physician, mathematician, and professional gambler who helped develop the idea that chance actually can be measured. They describe how later thinkers showed how the judgment of chance also can be measured, how frequency is related to chance, and how chance, judgment, and frequency could be unified. Diaconis and Skyrms explain how Thomas Bayes laid the foundation of modern statistics, and they explore David Hume’s problem of induction, Andrey Kolmogorov’s general mathematical framework for probability, the application of computability to chance, and why chance is essential to modern physics. A final idea—that we are psychologically predisposed to error when judging chance—is taken up through the work of Daniel Kahneman and Amos Tversky. Complete with a brief probability refresher, Ten Great Ideas about Chance is certain to be a hit with anyone who wants to understand the secrets of probability and how they were discovered. |
| jaynes 2003 probability theory the logic of science: Information Theory, Inference and Learning Algorithms David J. C. MacKay, 2003-09-25 Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning. |
| jaynes 2003 probability theory the logic of science: Handbook of Mathematical Geosciences Frits Agterberg, Qiuming Cheng, Bs Daya Sagar, 2020-10-09 This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors. |
| jaynes 2003 probability theory the logic of science: Probability Theory in Science and Engineering Edwin T. Jaynes, 1959 |
| jaynes 2003 probability theory the logic of science: Towards a Philosophy of Real Mathematics David Corfield, 2006-12-14 David Corfield provides a variety of innovative approaches to research in the philosophy of mathematics. His study ranges from an exploration of whether computers producing mathematical proofs or conjectures are doing real mathematics to the use of analogy; the prospects for a Bayesian confirmation theory; the notion of a mathematical research program; and the ways in which new concepts are justified. This highly original book will challenge philosophers as well as mathematicians to develop the broadest and most complete philosophical resources for research in their disciplines. |
| jaynes 2003 probability theory the logic of science: Quantum Mechanics, Volume 1 Claude Cohen-Tannoudji, Bernard Diu, Franck Laloë, 2019-12-04 This new edition of the unrivalled textbook introduces the fundamental concepts of quantum mechanics such as waves, particles and probability before explaining the postulates of quantum mechanics in detail. In the proven didactic manner, the textbook then covers the classical scope of introductory quantum mechanics, namely simple two-level systems, the one-dimensional harmonic oscillator, the quantized angular momentum and particles in a central potential. The entire book has been revised to take into account new developments in quantum mechanics curricula. The textbook retains its typical style also in the new edition: it explains the fundamental concepts in chapters which are elaborated in accompanying complements that provide more detailed discussions, examples and applications. * The quantum mechanics classic in a new edition: written by 1997 Nobel laureate Claude Cohen-Tannoudji and his colleagues Bernard Diu and Franck Laloë * As easily comprehensible as possible: all steps of the physical background and its mathematical representation are spelled out explicitly * Comprehensive: in addition to the fundamentals themselves, the book contains more than 350 worked examples plus exercises Claude Cohen-Tannoudji was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris where he also studied and received his PhD in 1962. In 1973 he became Professor of atomic and molecular physics at the Collège des France. His main research interests were optical pumping, quantum optics and atom-photon interactions. In 1997, Claude Cohen-Tannoudji, together with Steven Chu and William D. Phillips, was awarded the Nobel Prize in Physics for his research on laser cooling and trapping of neutral atoms. Bernard Diu was Professor at the Denis Diderot University (Paris VII). He was engaged in research at the Laboratory of Theoretical Physics and High Energy where his focus was on strong interactions physics and statistical mechanics. Franck Laloë was a researcher at the Kastler-Brossel laboratory of the Ecole Normale Supérieure in Paris. His first assignment was with the University of Paris VI before he was appointed to the CNRS, the French National Research Center. His research was focused on optical pumping, statistical mechanics of quantum gases, musical acoustics and the foundations of quantum mechanics. |
| jaynes 2003 probability theory the logic of science: Outline of Crystallography for Biologists David Merwyn Blow, 2002-04-11 X-ray crystallography is the main method used to determine the structure of biological molecules. X-ray crystallography is explained without maths and reading this text allows biologists to assess the quality and accuracy of biological structures. |
| jaynes 2003 probability theory the logic of science: The Theory That Would Not Die Sharon Bertsch McGrayne, 2011-05-17 This account of how a once reviled theory, Baye’s rule, came to underpin modern life is both approachable and engrossing (Sunday Times). A New York Times Book Review Editors’ Choice Bayes' rule appears to be a straightforward, one-line theorem: by updating our initial beliefs with objective new information, we get a new and improved belief. To its adherents, it is an elegant statement about learning from experience. To its opponents, it is subjectivity run amok. In the first-ever account of Bayes' rule for general readers, Sharon Bertsch McGrayne explores this controversial theorem and the generations-long human drama surrounding it. McGrayne traces the rule’s discovery by an 18th century amateur mathematician through its development by French scientist Pierre Simon Laplace. She reveals why respected statisticians rendered it professionally taboo for 150 years—while practitioners relied on it to solve crises involving great uncertainty and scanty information, such as Alan Turing's work breaking Germany's Enigma code during World War II. McGrayne also explains how the advent of computer technology in the 1980s proved to be a game-changer. Today, Bayes' rule is used everywhere from DNA de-coding to Homeland Security. Drawing on primary source material and interviews with statisticians and other scientists, The Theory That Would Not Die is the riveting account of how a seemingly simple theorem ignited one of the greatest controversies of all time. |
Jaynes Corporation | Southwest General Contractor
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Construction in Albuquerque NM | Jaynes Corporation
Jaynes completes construction projects in Albuquerque for doctors and patients, students and teachers, business leaders and the community.
Artesia Recreation Center | Jaynes Corporation
Jaynes has a long and successful history with large projects in Artesia, including the Artesia Public Library, the Artesia Aquatic Center, multiple projects for the Artesia Public Schools, the …
Los Altos Softball Complex | Best Of 2024 | Jaynes
Construction of the Los Altos Softball Complex Phase 1 was completed by Jaynes in July 2023 amid rave reviews from players, teams, and park visitors. The renovated facility soon delivered …
New Mexico Contractor | Jaynes Corporation | Farmington
Trust Jaynes is a builder you can trust. Our commitment to project transparency has set apart in the communities where we work. Using cloud based technologies project stakeholders can …
Jaynes Leadership Team | Jaynes Corporation
Nov 1, 2023 · Leadership at Jaynes is marked by diversity of experience, depth of knowledge, and a relentless commitment to lead by example. Together, our leadership team represents more …
The Impact of Jaynes’ 100% Employee Ownership on Jaynes’ …
In our previous post on Jaynes’ Employee Stock Ownership Plan (ESOP) and 100% employee ownership, we focused on what that delivered to Jaynes’ customers. Academic research has …
Living the Jaynes Way
For Jaynes, our values aren’t something we aspire to. They’re the essence of who we are. We’ve distilled our culture and principles into what we call The Jaynes Way, which is a symbol and …
Las Cruces Office | Jaynes Corporation
Since then, we have been a part of projects like the Las Cruces Convention Center, Las Cruces City Hall, Lincoln County Medical Center, Artesia General Hospital Renovation, and Lohman …
Texas Contractor | Jaynes Corporation | El Paso
Jaynes completes construction projects in El Paso for doctors and patients, students and teachers, business leaders and the community.
Jaynes Corporation | Southwest General Contractor
Seven decades of construction experience and industry leadership has provided the confluence of what has become our mantra. Build. Lead. Grow.
Construction in Albuquerque NM | Jaynes Corporation
Jaynes completes construction projects in Albuquerque for doctors and patients, students and teachers, business leaders and the community.
Artesia Recreation Center | Jaynes Corporation
Jaynes has a long and successful history with large projects in Artesia, including the Artesia Public Library, the Artesia Aquatic Center, multiple projects for the Artesia Public Schools, the …
Los Altos Softball Complex | Best Of 2024 | Jaynes
Construction of the Los Altos Softball Complex Phase 1 was completed by Jaynes in July 2023 amid rave reviews from players, teams, and park visitors. The renovated facility soon delivered …
New Mexico Contractor | Jaynes Corporation | Farmington
Trust Jaynes is a builder you can trust. Our commitment to project transparency has set apart in the communities where we work. Using cloud based technologies project stakeholders can …
Jaynes Leadership Team | Jaynes Corporation
Nov 1, 2023 · Leadership at Jaynes is marked by diversity of experience, depth of knowledge, and a relentless commitment to lead by example. Together, our leadership team represents more …
The Impact of Jaynes’ 100% Employee Ownership on Jaynes’ …
In our previous post on Jaynes’ Employee Stock Ownership Plan (ESOP) and 100% employee ownership, we focused on what that delivered to Jaynes’ customers. Academic research has …
Living the Jaynes Way
For Jaynes, our values aren’t something we aspire to. They’re the essence of who we are. We’ve distilled our culture and principles into what we call The Jaynes Way, which is a symbol and …
Las Cruces Office | Jaynes Corporation
Since then, we have been a part of projects like the Las Cruces Convention Center, Las Cruces City Hall, Lincoln County Medical Center, Artesia General Hospital Renovation, and Lohman …
Texas Contractor | Jaynes Corporation | El Paso
Jaynes completes construction projects in El Paso for doctors and patients, students and teachers, business leaders and the community.
