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Book
Science and scepticism
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ISBN: 069110171X 0691072949 0691612188 1400857368 1306993245 9780691072944 9781400857364 9780691101712 9780691612188 Year: 1984 Publisher: Princeton, New Jersey

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Abstract

This book contains important technical innovations, including comparative measures for the testable content, depth, and unity of scientific theories.Originally published in 1984.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Keywords

Science --- Skepticism --- Rationalism --- Knowledge, Theory of --- Philosophy --- -Skepticism --- Scepticism --- Unbelief --- Agnosticism --- Belief and doubt --- Free thought --- Natural science --- Science of science --- Sciences --- Religion --- Deism --- Realism --- Epistemology --- Theory of knowledge --- Psychology --- Knowledge, Theory of. --- Rationalism. --- Skepticism. --- Philosophy. --- Normal science --- Philosophy of science --- wetenschap --- filosofie --- maatschappijkritiek --- Science - Philosophy --- A priori and a posteriori. --- A priori probability. --- Ad hoc. --- Ad hominem. --- Agnosticism. --- Almost surely. --- Analytic–synthetic distinction. --- Anti-realism. --- Antireductionism. --- Asymmetry. --- Atomism. --- Axiom. --- Bayesian probability. --- Bayesian statistics. --- Bayesian. --- Begging the question. --- Certainty. --- Circular reasoning. --- Classical logic. --- Classical physics. --- Contradiction. --- David Hume. --- Deductive reasoning. --- Deductive-nomological model. --- Determinism. --- Dialectician. --- Edmund Husserl. --- Explanation. --- Explanatory power. --- Extrapolation. --- Fair coin. --- Fallibilism. --- Falsifiability. --- Falsity. --- Fideism. --- First principle. --- Form of life (philosophy). --- Free parameter. --- Good and evil. --- Hilary Putnam. --- Holism. --- Hypothesis. --- Idealism. --- Impenetrability. --- Inductive reasoning. --- Inductivism. --- Inference. --- Infinite regress. --- Instance (computer science). --- Is–ought problem. --- J. L. Austin. --- Logical reasoning. --- Lottery paradox. --- Magical thinking. --- Materialism. --- Michael Polanyi. --- Modern physics. --- Modus tollens. --- Mutual exclusivity. --- Neutral monism. --- Occam's razor. --- Ontology. --- Ordinary language philosophy. --- Ought implies can. --- Paradox. --- Persuasive definition. --- Phenomenalism. --- Philosopher. --- Phrenology. --- Possible world. --- Posterior probability. --- Pre-established harmony. --- Prediction. --- Predictive power. --- Premise. --- Probabilism. --- Probability. --- Problem of induction. --- Pseudoscience. --- Pyrrhonism. --- Rationality. --- Reality. --- Reason. --- Received view. --- Reductionism. --- Relativism. --- Requirement. --- Richard Jeffrey. --- Scientific realism. --- Scientific theory. --- Sensationalism. --- Suggestion. --- Tautology (rhetoric). --- Testability. --- Theory. --- Transcendental arguments. --- Truism. --- Verisimilitude. --- Wrong direction.


Book
Maxwell's Demon : Entropy, Information, Computing
Authors: ---
ISBN: 1400861527 0691605467 9781400861521 0691087261 069108727X 9780691605463 9780691087269 0691087261 9780691087276 069108727X 0691634432 Year: 2014 Publisher: Princeton, NJ : Princeton University Press,

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About 120 years ago, James Clerk Maxwell introduced his now legendary hypothetical "demon" as a challenge to the integrity of the second law of thermodynamics. Fascination with the demon persisted throughout the development of statistical and quantum physics, information theory, and computer science--and linkages have been established between Maxwell's demon and each of these disciplines. The demon's seductive quality makes it appealing to physical scientists, engineers, computer scientists, biologists, psychologists, and historians and philosophers of science. Until now its important source material has been scattered throughout diverse journals.This book brings under one cover twenty-five reprints, including seminal works by Maxwell and William Thomson; historical reviews by Martin Klein, Edward Daub, and Peter Heimann; information theoretic contributions by Leo Szilard, Leon Brillouin, Dennis Gabor, and Jerome Rothstein; and innovations by Rolf Landauer and Charles Bennett illustrating linkages with the limits of computation. An introductory chapter summarizes the demon's life, from Maxwell's illustration of the second law's statistical nature to the most recent "exorcism" of the demon based on a need periodically to erase its memory. An annotated chronological bibliography is included.Originally published in 1990.The Princeton Legacy Library uses the latest print-on-demand technology to again make available previously out-of-print books from the distinguished backlist of Princeton University Press. These editions preserve the original texts of these important books while presenting them in durable paperback and hardcover editions. The goal of the Princeton Legacy Library is to vastly increase access to the rich scholarly heritage found in the thousands of books published by Princeton University Press since its founding in 1905.

Keywords

Thermodynamics. --- Chemistry, Physical and theoretical --- Dynamics --- Mechanics --- Physics --- Heat --- Heat-engines --- Quantum theory --- Maxwell's demon. --- Adiabatic process. --- Automaton. --- Available energy (particle collision). --- Billiard-ball computer. --- Black hole information paradox. --- Black hole thermodynamics. --- Black-body radiation. --- Boltzmann's entropy formula. --- Boyle's law. --- Calculation. --- Carnot's theorem (thermodynamics). --- Catalysis. --- Chaos theory. --- Computation. --- Copying. --- Creation and annihilation operators. --- Digital physics. --- Dissipation. --- Distribution law. --- Domain wall. --- EPR paradox. --- Energy level. --- Entropy of mixing. --- Entropy. --- Exchange interaction. --- Expectation value (quantum mechanics). --- Extrapolation. --- Fair coin. --- Fermi–Dirac statistics. --- Gibbs free energy. --- Gibbs paradox. --- Guessing. --- Halting problem. --- Hamiltonian mechanics. --- Heat engine. --- Heat. --- Helmholtz free energy. --- Ideal gas. --- Idealization. --- Information theory. --- Instant. --- Internal energy. --- Irreversible process. --- James Prescott Joule. --- Johnson–Nyquist noise. --- Kinetic theory of gases. --- Laws of thermodynamics. --- Least squares. --- Loschmidt's paradox. --- Ludwig Boltzmann. --- Maxwell–Boltzmann distribution. --- Mean free path. --- Measurement. --- Mechanical equivalent of heat. --- Microscopic reversibility. --- Molecule. --- Negative temperature. --- Negentropy. --- Newton's law of universal gravitation. --- Nitrous oxide. --- Non-equilibrium thermodynamics. --- Old quantum theory. --- Particle in a box. --- Perpetual motion. --- Photon. --- Probability. --- Quantity. --- Quantum limit. --- Quantum mechanics. --- Rectangular potential barrier. --- Result. --- Reversible computing. --- Reversible process (thermodynamics). --- Richard Feynman. --- Rolf Landauer. --- Rudolf Clausius. --- Scattering. --- Schrödinger equation. --- Second law of thermodynamics. --- Self-information. --- Spontaneous process. --- Standard state. --- Statistical mechanics. --- Superselection. --- Temperature. --- Theory of heat. --- Theory. --- Thermally isolated system. --- Thermodynamic equilibrium. --- Thermodynamic system. --- Thought experiment. --- Turing machine. --- Ultimate fate of the universe. --- Uncertainty principle. --- Unitarity (physics). --- Van der Waals force. --- Wave function collapse. --- Work output.


Book
What makes us smart : the computational logic of human cognition
Author:
ISBN: 0691225990 Year: 2021 Publisher: Princeton : Princeton University Press,

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At the heart of human intelligence rests a fundamental puzzle: How are we incredibly smart and stupid at the same time? No existing machine can match the power and flexibility of human perception, language, and reasoning. Yet, we routinely commit errors that reveal the failures of our thought processes. 'What Makes Us Smart' makes sense of this paradox by arguing that our cognitive errors are not haphazard. Rather, they are the inevitable consequences of a brain optimized for efficient inference and decision making within the constraints of time, energy, and memory - in other words, data and resource limitations. Framing human intelligence in terms of these constraints, Samuel Gershman shows how a deeper computational logic underpins the 'stupid' errors of human cognition.

Keywords

Cognition --- Cognitive psychology. --- Age factors. --- Psychology, Cognitive --- Cognitive science --- Psychology --- Age factors in cognition --- Ability, Influence of age on --- Cognition. --- Intellect. --- Human intelligence --- Intelligence --- Mind --- Ability --- Thought and thinking --- Accuracy and precision. --- Action potential. --- Ad hoc hypothesis. --- Ad hominem. --- Adaptive bias. --- Almost surely. --- Alternative hypothesis. --- Altruism. --- Ambiguity. --- Analogy. --- Anecdote. --- Approximation. --- Attractiveness. --- Bayes' theorem. --- Bayesian inference. --- Bayesian probability. --- Bayesian. --- Behavior. --- Circular reasoning. --- Cognitive flexibility. --- Cognitive style. --- Commitment device. --- Confidence. --- Confirmation bias. --- Conspiracy theory. --- Controllability. --- Counterintuitive. --- Credibility. --- Decision-making. --- Effectiveness. --- Efficacy. --- Efficiency. --- Efficient coding hypothesis. --- Efficient frontier. --- Estimation. --- Expected value. --- Explanation. --- Fair coin. --- Fair market value. --- Gimmick. --- Guessing. --- Heuristic. --- Hot Hand. --- Human intelligence. --- Hypothesis. --- Illusion of control. --- Inductive bias. --- Inference. --- Intelligent design. --- Learnability. --- Lightness (philosophy). --- Likelihood function. --- Logical extreme. --- Logical reasoning. --- Moral hazard. --- Motivated reasoning. --- Mutual exclusivity. --- Natural approach. --- Normative. --- Observation. --- Observational learning. --- Of Miracles. --- Opportunity cost. --- Optimism bias. --- Optimism. --- Our Choice. --- Pairwise comparison. --- Perfect rationality. --- Physical attractiveness. --- Point estimation. --- Politeness. --- Positive feedback. --- Predictability. --- Prediction. --- Predictive coding. --- Predictive power. --- Principle of rationality. --- Prior probability. --- Probability. --- Prosocial behavior. --- Quantity. --- Rational agent. --- Rational choice theory. --- Rationality. --- Reason. --- Reinforcement learning. --- Result. --- Self-control. --- Sophistication. --- Spontaneous recovery. --- Strong inference. --- Suggestion. --- Theory. --- Thought. --- Truth value. --- Uncertainty. --- Utility. --- Value of information. --- With high probability. --- PSYCHOLOGY / Cognitive Psychology & Cognition --- COMPUTERS / Logic Design


Book
Econometric modeling : a likelihood approach
Authors: ---
ISBN: 1400845653 Year: 2007 Publisher: Princeton ; Oxford : Princeton University Press,

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Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointe.

Keywords

Econometric models. --- Econometrics. --- Accuracy and precision. --- Asymptotic distribution. --- Autocorrelation. --- Autoregressive conditional heteroskedasticity. --- Autoregressive model. --- Bayesian statistics. --- Bayesian. --- Bernoulli distribution. --- Bias of an estimator. --- Calculation. --- Central limit theorem. --- Chow test. --- Cointegration. --- Conditional expectation. --- Conditional probability distribution. --- Confidence interval. --- Confidence region. --- Correlation and dependence. --- Correlogram. --- Count data. --- Cross-sectional data. --- Cross-sectional regression. --- Distribution function. --- Dummy variable (statistics). --- Econometric model. --- Empirical distribution function. --- Equation. --- Error term. --- Estimation. --- Estimator. --- Exogeny. --- Exploratory data analysis. --- F-distribution. --- F-test. --- Fair coin. --- Forecast error. --- Forecasting. --- Granger causality. --- Heteroscedasticity. --- Inference. --- Instrumental variable. --- Joint probability distribution. --- Law of large numbers. --- Least absolute deviations. --- Least squares. --- Likelihood function. --- Likelihood-ratio test. --- Linear regression. --- Logistic regression. --- Lucas critique. --- Marginal distribution. --- Markov process. --- Mathematical optimization. --- Maximum likelihood estimation. --- Model selection. --- Monte Carlo method. --- Moving-average model. --- Multiple correlation. --- Multivariate normal distribution. --- Nonparametric regression. --- Normal distribution. --- Normality test. --- One-Tailed Test. --- Opportunity cost. --- Orthogonalization. --- P-value. --- Parameter. --- Partial correlation. --- Poisson regression. --- Probability. --- Probit model. --- Quantile. --- Quantity. --- Quasi-likelihood. --- Random variable. --- Regression analysis. --- Residual sum of squares. --- Round-off error. --- Seemingly unrelated regressions. --- Selection bias. --- Simple linear regression. --- Skewness. --- Standard deviation. --- Standard error. --- Stationary process. --- Statistic. --- Student's t-test. --- Sufficient statistic. --- Summary statistics. --- T-statistic. --- Test statistic. --- Time series. --- Type I and type II errors. --- Unit root test. --- Unit root. --- Utility. --- Variable (mathematics). --- Variance. --- Vector autoregression. --- White test.

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