Probability Theory: The Logic of ScienceCambridge University Press, 10/04/2003 The standard rules of probability can be interpreted as uniquely valid principles in logic. In this book, E. T. Jaynes dispels the imaginary distinction between 'probability theory' and 'statistical inference', leaving a logical unity and simplicity, which provides greater technical power and flexibility in applications. This book goes beyond the conventional mathematics of probability theory, viewing the subject in a wider context. New results are discussed, along with applications of probability theory to a wide variety of problems in physics, mathematics, economics, chemistry and biology. It contains many exercises and problems, and is suitable for use as a textbook on graduate level courses involving data analysis. The material is aimed at readers who are already familiar with applied mathematics at an advanced undergraduate level or higher. The book will be of interest to scientists working in any area where inference from incomplete information is necessary. |
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الصفحة 9
... robot we shall study. Comparing its reasoning with yours, if you find no resemblance you are in turn free to reject our robot and design a different one more to your liking. But if you find a very strong resemblance, and decide that you ...
... robot we shall study. Comparing its reasoning with yours, if you find no resemblance you are in turn free to reject our robot and design a different one more to your liking. But if you find a very strong resemblance, and decide that you ...
الصفحة 17
... robot must assign some degree of plausibility, based on the evidence we have given it; and whenever it receives new evidence it must revise these assignments to take that new evidence into account. In order that these plausibility ...
... robot must assign some degree of plausibility, based on the evidence we have given it; and whenever it receives new evidence it must revise these assignments to take that new evidence into account. In order that these plausibility ...
الصفحة 18
... robot to undergo the agony of reasoning from impossible or mutually contradictory premises; there could be no 'correct' answer. Thus, we make no attempt to define A\BC when B and C are mutually contradictory. Whenever such a symbol ...
... robot to undergo the agony of reasoning from impossible or mutually contradictory premises; there could be no 'correct' answer. Thus, we make no attempt to define A\BC when B and C are mutually contradictory. Whenever such a symbol ...
الصفحة 19
... robot is completely nonideological. The robot always represents equivalent states of knowledge by equivalent plausibility assignments. That is, if in two problems (IIIc) the robot 's state of knowledge is the same (except perhaps for ...
... robot is completely nonideological. The robot always represents equivalent states of knowledge by equivalent plausibility assignments. That is, if in two problems (IIIc) the robot 's state of knowledge is the same (except perhaps for ...
الصفحة 20
... robot to adopt any of these more 'human' features arising from the other coordinates. It is just the fact that computers do not get confused by emotional factors, do not get bored with a lengthy problem, do not pursue hidden motives ...
... robot to adopt any of these more 'human' features arising from the other coordinates. It is just the fact that computers do not get confused by emotional factors, do not get bored with a lengthy problem, do not pursue hidden motives ...
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عبارات ومصطلحات مألوفة
analysis appears applications argument Bayes binomial calculation Chapter coin common sense conclusions consider Cox's theorems criterion data set decision theory defined density derivation equal equations error estimate evidence example expected fact finite Fisher frequency Gaussian give given Harold Jeffreys hypothesis improper prior independent induction inductive reasoning inference infinite sets integral intuitive Jeffreys knowledge Laplace Laplace's likelihood likelihood function limit loss function mathematical maximum entropy mean measure noise normal notation noted nuisance parameters numerical values observed paradox physical plausible possible posterior distribution posterior pdf posterior probability predictions principle principle of indifference prior information prior probability probability assignment probability distribution probability theory problem product rule propositions random experiment reasoning relevant result robot rules of probability sampling distribution solution specified statement sufficient statistic suppose tell theorem theory as logic toss trials true widgets