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 xiii
... common sense at Rothamsted 532 17.8. 1 The Bayesian safety device 532 17.9 Missing data 533 17.10 Trend and seasonality in time series 534 1 7. 1 0. 1 Orthodox methods 535 17.10.2 The Bayesian method 536 17. 10.3 Comparison of Bayesian ...
... common sense at Rothamsted 532 17.8. 1 The Bayesian safety device 532 17.9 Missing data 533 17.10 Trend and seasonality in time series 534 1 7. 1 0. 1 Orthodox methods 535 17.10.2 The Bayesian method 536 17. 10.3 Comparison of Bayesian ...
الصفحة xix
... common sense' into a set of elementary qualitative desiderata and showed that mathematicians had been using them all along to guide the early stages of discovery, which necessarily precede the. 1 By 'inference' we mean simply: deductive ...
... common sense' into a set of elementary qualitative desiderata and showed that mathematicians had been using them all along to guide the early stages of discovery, which necessarily precede the. 1 By 'inference' we mean simply: deductive ...
الصفحة xxvii
... common euphemism, 'filtered') by processing according to false assumptions ... sense. There are two more, even stronger, reasons for placing our primary ... sense of the real world, tie their arguments to unrealistic premises and thus ...
... common euphemism, 'filtered') by processing according to false assumptions ... sense. There are two more, even stronger, reasons for placing our primary ... sense of the real world, tie their arguments to unrealistic premises and thus ...
الصفحة 4
... common sense, obeying the weak syllogism, may induce us to change our plans and behave as if we believed that it will, if those clouds are sufficiently dark. This example shows also that the major premise, 'if A then B' expresses B only ...
... common sense, obeying the weak syllogism, may induce us to change our plans and behave as if we believed that it will, if those clouds are sufficiently dark. This example shows also that the major premise, 'if A then B' expresses B only ...
الصفحة 6
... common sense. The mathematician George Polya (1945, 1954) wrote three books about plausible reasoning, pointing out a wealth of interesting examples and showing that there are definite rules by which we do plausible reasoning (although ...
... common sense. The mathematician George Polya (1945, 1954) wrote three books about plausible reasoning, pointing out a wealth of interesting examples and showing that there are definite rules by which we do plausible reasoning (although ...
المحتوى
CLXXI | 341 |
CLXXII | 343 |
CLXXIII | 345 |
CLXXIV | 346 |
CLXXV | 351 |
CLXXVI | 354 |
CLXXVII | 355 |
CLXXVIII | 358 |
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XXIX | 66 |
XXX | 68 |
XXXII | 69 |
XXXIII | 72 |
XXXIV | 73 |
XXXV | 75 |
XXXVI | 81 |
XXXVII | 82 |
XXXVIII | 84 |
XXXIX | 86 |
XL | 87 |
XLI | 90 |
XLII | 97 |
XLIII | 98 |
XLIV | 101 |
XLV | 107 |
XLVI | 109 |
XLVII | 112 |
XLVIII | 115 |
XLIX | 116 |
L | 117 |
LI | 119 |
LIII | 120 |
LIV | 122 |
LVI | 126 |
LVII | 132 |
LVIII | 133 |
LIX | 135 |
LX | 137 |
LXI | 140 |
LXII | 142 |
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LXV | 146 |
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LXIX | 152 |
LXX | 154 |
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LXXIV | 163 |
LXXVI | 166 |
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LXXVIII | 168 |
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LXXXII | 179 |
LXXXIII | 181 |
LXXXIV | 183 |
LXXXV | 186 |
LXXXVII | 188 |
LXXXVIII | 190 |
LXXXIX | 192 |
XC | 193 |
XCI | 195 |
XCII | 198 |
XCIII | 199 |
XCIV | 200 |
XCV | 202 |
XCVI | 203 |
XCVII | 205 |
XCVIII | 207 |
XCIX | 210 |
C | 211 |
CI | 213 |
CII | 215 |
CIII | 216 |
CIV | 218 |
CV | 219 |
CVI | 220 |
CVII | 221 |
CVIII | 222 |
CIX | 224 |
CX | 227 |
CXI | 229 |
CXII | 231 |
CXIII | 233 |
CXIV | 234 |
CXV | 235 |
CXVI | 236 |
CXVII | 238 |
CXVIII | 239 |
CXIX | 240 |
CXX | 243 |
CXXI | 245 |
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CXXIV | 248 |
CXXV | 249 |
CXXVI | 250 |
CXXVII | 253 |
CXXVIII | 254 |
CXXIX | 256 |
CXXX | 257 |
CXXXI | 260 |
CXXXII | 261 |
CXXXIII | 262 |
CXXXIV | 264 |
CXXXVI | 266 |
CXXXVII | 267 |
CXXXIX | 270 |
CXL | 271 |
CXLI | 274 |
CXLII | 276 |
CXLIII | 277 |
CXLIV | 280 |
CXLV | 281 |
CXLVI | 282 |
CXLVII | 285 |
CXLVIII | 289 |
CXLIX | 290 |
CL | 292 |
CLI | 293 |
CLII | 296 |
CLIII | 300 |
CLIV | 302 |
CLV | 304 |
CLVI | 305 |
CLVII | 310 |
CLVIII | 312 |
CLIX | 314 |
CLX | 315 |
CLXI | 317 |
CLXII | 320 |
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CLXV | 326 |
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CLXVII | 329 |
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CLXIX | 335 |
CLXX | 338 |
CLXXIX | 365 |
CLXXX | 370 |
CLXXXI | 372 |
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CLXXXIV | 378 |
CLXXXVI | 382 |
CLXXXVIII | 386 |
CLXXXIX | 394 |
CXC | 397 |
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CXCV | 404 |
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CC | 417 |
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CCL | 531 |
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CCXC | 601 |
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CCXCVI | 607 |
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CCXCIX | 614 |
CCC | 615 |
CCCI | 617 |
CCCII | 619 |
CCCIII | 620 |
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CCCXXXVIII | 721 |
CCCXXXIX | 724 |
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