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Probabilities --- Philosophy --- Philosophy. --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Probabilities - Philosophy
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Not all scientific explanations work by describing causal connections between events or the world's overall causal structure. Some mathematical proofs explain why the theorems being proved hold. In this book, Marc Lange proposes philosophical accounts of many kinds of non-causal explanations in science and mathematics. These topics have been unjustly neglected in the philosophy of science and mathematics. One important kind of non-causal scientific explanation is termed explanation by constraint. These explanations work by providing information about what makes certain facts especially inevitable - more necessary than the ordinary laws of nature connecting causes to their effects. Facts explained in this way transcend the hurly-burly of cause and effect. Many physicists have regarded the laws of kinematics, the great conservation laws, the coordinate transformations, and the parallelogram of forces as having explanations by constraint. This book presents an original account of explanations by constraint, concentrating on a variety of examples from classical physics and special relativity. This book also offers original accounts of several other varieties of non-causal scientific explanation. Dimensional explanations work by showing how some law of nature arises merely from the dimensional relations among the quantities involved. Really statistical explanations include explanations that appeal to regression toward the mean and other canonical manifestations of chance. Lange provides an original account of what makes certain mathematical proofs but not others explain what they prove. Mathematical explanation connects to a host of other important mathematical ideas, including coincidences in mathematics, the significance of giving multiple proofs of the same result, and natural properties in mathematics. Introducing many examples drawn from actual science and mathematics, with extended discussions of examples from Lagrange, Desargues, Thomson, Sylvester, Maxwell, Rayleigh, Einstein, and Feynman, Because Without Cause's proposals and examples should set the agenda for future work on non-causal explanation.
Probabilities --- Conditional expectations (Mathematics) --- Science --- Mathematics --- Philosophy --- Maematics --- PHILOSOPHY / Logic. --- SCIENCE / Philosophy & Social Aspects. --- Conditional expectations (Mathematics). --- Conditional expectations (mathematics). --- Philosophy / logic. --- Science / philosophy & social aspects. --- Philosophy of science --- Philosophy. --- Probabilities - Philosophy --- Science - Philosophy --- Mathematics - Philosophy
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Our beliefs come in degrees. I'm 70% confident it will rain tomorrow, and 0.001% sure my lottery ticket will win. What's more, we think these degrees of belief should abide by certain principles if they are to be rational. For instance, you shouldn't believe that a person's taller than 6ft more strongly than you believe that they're taller than 5ft, since the former entails the latter. In Dutch Book arguments, we try to establish the principles of rationality for degrees of belief by appealing to their role in guiding decisions. In particular, we show that degrees of belief that don't satisfy the principles will always guide action in some way that is bad or undesirable. In this Element, we present Dutch Book arguments for the principles of Probabilism, Conditionalization, and the Reflection Principle, among others, and we formulate and consider the most serious objections to them. --
Probabilities --- Knowledge, Theory of --- Philosophy --- Probabilities - Philosophy --- Probabilities. --- Bayesian statistical decision theory. --- Knowledge, Theory of. --- Bayes' solution --- Bayesian analysis --- Statistical decision --- Epistemology --- Theory of knowledge --- Psychology --- Probability --- Statistical inference --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk
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How should the concept of evidence be understood? And how does the concept of evidence apply to the controversy about creationism as well as to work in evolutionary biology about natural selection and common ancestry? In this rich and wide-ranging book, Elliott Sober investigates general questions about probability and evidence and shows how the answers he develops to those questions apply to the specifics of evolutionary biology. Drawing on a set of fascinating examples, he analyzes whether claims about intelligent design are untestable; whether they are discredited by the fact that many adaptations are imperfect; how evidence bears on whether present species trace back to common ancestors; how hypotheses about natural selection can be tested, and many other issues. His book will interest all readers who want to understand philosophical questions about evidence and evolution, as they arise both in Darwin's work and in contemporary biological research.
Philosophy of nature --- Logic --- Evolution. Phylogeny --- Evolution (Biology) --- Natural selection --- Evidence --- Probabilities --- Philosophy --- Evidence. --- Philosophy. --- Probability --- Statistical inference --- Proof --- Combinations --- Mathematics --- Chance --- Least squares --- Mathematical statistics --- Risk --- Belief and doubt --- Faith --- Truth --- Arts and Humanities --- Evolution (Biology) - Philosophy --- Natural selection - Philosophy --- Probabilities - Philosophy
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