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Author: Martin Smith
Publisher: Oxford University Press
ISBN: 0191071633
Category : Philosophy
Languages : en
Pages : 256
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Book Description
Martin Smith explores a question central to philosophy—namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In the present book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it—roughly, one's evidence must make the falsity of that proposition abnormal in the sense of calling for special, independent explanation. This conception of justification bears upon a range of topics in epistemology and beyond, including the relation between justification and knowledge, the force of statistical evidence, the problem of scepticism, the lottery and preface paradoxes, the viability of multiple premise closure, the internalist/externalist debate, the psychology of human reasoning, and the relation between belief and degrees of belief. Ultimately, this way of looking at justification guides us to a new, unfamiliar picture of how we should respond to our evidence and manage our own fallibility. This picture is developed here.
Author: Martin Smith
Publisher: Oxford University Press
ISBN: 0191071633
Category : Philosophy
Languages : en
Pages : 256
Get Book
Book Description
Martin Smith explores a question central to philosophy—namely, what does it take for a belief to be justified or rational? According to a widespread view, whether one has justification for believing a proposition is determined by how probable that proposition is, given one's evidence. In the present book this view is rejected and replaced with another: in order for one to have justification for believing a proposition, one's evidence must normically support it—roughly, one's evidence must make the falsity of that proposition abnormal in the sense of calling for special, independent explanation. This conception of justification bears upon a range of topics in epistemology and beyond, including the relation between justification and knowledge, the force of statistical evidence, the problem of scepticism, the lottery and preface paradoxes, the viability of multiple premise closure, the internalist/externalist debate, the psychology of human reasoning, and the relation between belief and degrees of belief. Ultimately, this way of looking at justification guides us to a new, unfamiliar picture of how we should respond to our evidence and manage our own fallibility. This picture is developed here.
Author: Ludomir M. Laudański
Publisher: Springer Science & Business Media
ISBN: 3642256961
Category : Mathematics
Languages : en
Pages : 314
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Book Description
„Between Certainty & Uncertainty” is a one-of–a-kind short course on statistics for students, engineers and researchers. It is a fascinating introduction to statistics and probability with notes on historical origins and 80 illustrative numerical examples organized in the five units: · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 1 Descriptive Statistics: Compressing small samples, basic averages - mean and variance, their main properties including God’s proof; linear transformations and z-scored statistics . · Chapter 2 Grouped data: Udny Yule’s concept of qualitative and quantitative variables. Grouping these two kinds of data. Graphical tools. Combinatorial rules and qualitative variables. Designing frequency histogram. Direct and coded evaluation of quantitative data. Significance of percentiles. · Chapter 3 Regression and correlation: Geometrical distance and equivalent distances in two orthogonal directions as a prerequisite to the concept of two regression lines. Misleading in interpreting two regression lines. Derivation of the two regression lines. Was Hubble right? Houbolt’s cloud. What in fact measures the correlation coefficient? · Chapter 4 Binomial distribution: Middle ages origins of the binomials; figurate numbers and combinatorial rules. Pascal’s Arithmetical Triangle. Bernoulli’s or Poisson Trials? John Arbuthnot curing binomials. How Newton taught S. Pepys probability. Jacob Bernoulli’s Weak Law of Large Numbers and others. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace. · Chapter 5 Normal distribution and binomial heritage – Tables of the normal distribution. Abraham de Moivre and the second theorem of de Moivre-Laplace.
Author: Martin Smith
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Author: Barbara J. Shapiro
Publisher:
ISBN: 9780691053790
Category : England
Languages : en
Pages : 347
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Book Description
The Description for this book, Probability and Certainty in Seventeenth-Century England: A Study of the Relationships Between National Science, Religion, History, Law, and Literature, will be forthcoming.
Author: Krzysztof Burdzy
Publisher: World Scientific
ISBN: 9814273716
Category : Mathematics
Languages : en
Pages : 270
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Book Description
This volume represents a radical departure from the current philosophical duopoly in the area of foundations of probability, that is, the frequency and subjective theories. One of the main new ideas is a set of scientific laws of probability. The new laws are simple, intuitive and, last but not least, they agree well with the contents of current textbooks on probability. Another major new claim is that the OC frequency statisticsOCO has nothing in common with the OC frequency philosophy of probability, OCO contrary to popular belief. Similarly, contrary to the general perception, the OC Bayesian statisticsOCO shares nothing in common with the OC subjective philosophy of probability.OCO The book is non-partisan on the scientific side OCo it is supportive of both frequency statistics and Bayesian statistics. On the other hand, it contains well-documented and thoroughly-explained criticisms of the frequency and subjective philosophies of probability. Short reviews of other philosophical theories of probability and basic mathematical methods of probability and statistics are incorporated. The book includes substantial chapters on decision theory and teaching probability, and it is easily accessible to the general audience
Author: William Briggs
Publisher: Springer
ISBN: 3319397567
Category : Mathematics
Languages : en
Pages : 258
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Book Description
This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance." The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.
Author: Dawn Griffiths
Publisher: "O'Reilly Media, Inc."
ISBN: 059680086X
Category : Mathematics
Languages : en
Pages : 721
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Book Description
A comprehensive introduction to statistics that teaches the fundamentals with real-life scenarios, and covers histograms, quartiles, probability, Bayes' theorem, predictions, approximations, random samples, and related topics.
Author: Mark Burgess
Publisher: "O'Reilly Media, Inc."
ISBN: 1491923377
Category : Computers
Languages : en
Pages : 473
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Book Description
Quite soon, the world’s information infrastructure is going to reach a level of scale and complexity that will force scientists and engineers to approach it in an entirely new way. The familiar notions of command and control are being thwarted by realities of a faster, denser world of communication where choice, variety, and indeterminism rule. The myth of the machine that does exactly what we tell it has come to an end. What makes us think we can rely on all this technology? What keeps it together today, and how might it work tomorrow? Will we know how to build the next generation—or will we be lulled into a stupor of dependence brought about by its conveniences? In this book, Mark Burgess focuses on the impact of computers and information on our modern infrastructure by taking you from the roots of science to the principles behind system operation and design. To shape the future of technology, we need to understand how it works—or else what we don’t understand will end up shaping us. This book explores this subject in three parts: Part I, Stability: describes the fundamentals of predictability, and why we have to give up the idea of control in its classical meaning Part II, Certainty: describes the science of what we can know, when we don’t control everything, and how we make the best of life with only imperfect information Part III, Promises: explains how the concepts of stability and certainty may be combined to approach information infrastructure as a new kind of virtual material, restoring a continuity to human-computer systems so that society can rely on them.
Author: Emile Borel
Publisher:
ISBN:
Category : Certainty
Languages : en
Pages : 166
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Book Description
Author: Frank H. Knight
Publisher: Cosimo, Inc.
ISBN: 1602060053
Category : Business & Economics
Languages : en
Pages : 401
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Book Description
A timeless classic of economic theory that remains fascinating and pertinent today, this is Frank Knight's famous explanation of why perfect competition cannot eliminate profits, the important differences between "risk" and "uncertainty," and the vital role of the entrepreneur in profitmaking. Based on Knight's PhD dissertation, this 1921 work, balancing theory with fact to come to stunning insights, is a distinct pleasure to read. FRANK H. KNIGHT (1885-1972) is considered by some the greatest American scholar of economics of the 20th century. An economics professor at the University of Chicago from 1927 until 1955, he was one of the founders of the Chicago school of economics, which influenced Milton Friedman and George Stigler.
