|
|
|
|
| LEADER |
00000cam a2200000xa 4500 |
| 001 |
b12095107 |
| 003 |
CoU |
| 006 |
m o d |
| 007 |
cr ||||||||||| |
| 008 |
130208s1996 maua ob 001 0 eng d |
| 005 |
20230817224222.2 |
| 010 |
|
|
|z 96012572
|
| 019 |
|
|
|a 1170225135
|a 1171866135
|a 1286911927
|
| 020 |
|
|
|a 0262290995
|q (electronic bk.)
|
| 020 |
|
|
|a 9780262290999
|q (electronic bk.)
|
| 020 |
|
|
|z 026219368X
|
| 020 |
|
|
|z 9780262193689
|
| 035 |
|
|
|a (OCoLC)mit827013207
|
| 035 |
|
|
|a (OCoLC)827013207
|z (OCoLC)1170225135
|z (OCoLC)1171866135
|z (OCoLC)1286911927
|
| 037 |
|
|
|a MIT1403
|
| 040 |
|
|
|a IEEEE
|b eng
|e pn
|c IEEEE
|d OCLCF
|d OCLCQ
|d HRM
|d ESU
|d COO
|d MERER
|d OCLCQ
|d AU@
|d MITPR
|d LEAUB
|d HS0
|d OCLCQ
|d YDX
|d UKAHL
|d OCLCQ
|d OCLCO
|d LUN
|d SFB
|d VT2
|
| 049 |
|
|
|a GWRE
|
| 050 |
|
4 |
|a Q335
|b .S45 1996eb
|
| 100 |
1 |
|
|a Shafer, Glenn,
|d 1946-
|0 http://id.loc.gov/authorities/names/n90616807
|1 http://isni.org/isni/0000000109205158.
|
| 245 |
1 |
4 |
|a The art of causal conjecture
|h [electronic resource] /
|c Glenn Shafer.
|
| 260 |
|
|
|a Cambridge, Mass. :
|b MIT Press,
|c ©1996.
|
| 300 |
|
|
|a 1 online resource (xx, 511 pages) :
|b illustrations.
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent.
|
| 337 |
|
|
|a computer
|b c
|2 rdamedia.
|
| 338 |
|
|
|a online resource
|b cr
|2 rdacarrier.
|
| 490 |
1 |
|
|a Artificial intelligence.
|
| 504 |
|
|
|a Includes bibliographical references (pages 491-500) and index.
|
| 505 |
0 |
0 |
|g 1.
|t Introduction --
|g 2.
|t Event Trees --
|g 3.
|t Probability Trees --
|g 4.
|t Meaning of Probability --
|g 5.
|t Independent Events --
|g 6.
|t Events Tracking Events --
|g 7.
|t Events as Signs of Events --
|g 8.
|t Independent Variables --
|g 9.
|t Variables Tracking Variables --
|g 10.
|t Variables as Signs of Variables --
|g 11.
|t Abstract Theory of Event Trees --
|g 12.
|t Martingale Trees --
|g 13.
|t Refining --
|g 14.
|t Principles of Causal Conjecture --
|g 15.
|t Causal Models --
|g 16.
|t Representing Probability Trees --
|g App. A.
|t Huygens Probability Trees.
|
| 505 |
0 |
0 |
|g App. B.
|t Some Elements of Graph Theory --
|g App. C.
|t Some Elements of Order Theory --
|g App. D.
|t Sample-Space Framework for Probability --
|g App. E.
|t Prediction in Probability Spaces --
|g App. F.
|t Sample-Space Concepts of Independence --
|g App. G.
|t Prediction Diagrams --
|g App. H.
|t Abstract Stochastic Processes.
|
| 520 |
3 |
|
|a "In The Art of Causal Conjecture, Glenn Shafer lays out a new mathematical and philosophical foundation for probability and uses it to explain concepts of causality used in statistics, artificial intelligence, and philosophy. The various disciplines that use causal reasoning differ in the relative weight they put on security and precision of knowledge as opposed to timeliness of action. The natural and social sciences seek high levels of certainty in the identification of causes and high levels of precision in the measurement of their effects. The practical sciences--medicine, business, engineering, and artificial intelligence--must act on causal conjectures based on more limited knowledge. Shafer's understanding of causality contributes to both of these uses of causal reasoning. His language for causal explanation can guide statistical investigation in the natural and social sciences, and it can also be used to formulate assumptions of causal uniformity needed for decision making in the practical sciences. Causal ideas permeate the use of probability and statistics in all branches of industry, commerce, government, and science. The Art of Causal Conjecture shows that causal ideas can be equally important in theory. It does not challenge the maxim that causation cannot be proven from statistics alone, but by bringing causal ideas into the foundations of probability, it allows causal conjectures to be more clearly quantified, debated, and confronted by statistical evidence."
|
| 588 |
0 |
|
|a Print version record.
|
| 650 |
|
0 |
|a Artificial intelligence.
|0 http://id.loc.gov/authorities/subjects/sh85008180.
|
| 650 |
|
0 |
|a Causation.
|0 http://id.loc.gov/authorities/subjects/sh85021459.
|
| 650 |
|
0 |
|a Prediction (Logic)
|0 http://id.loc.gov/authorities/subjects/sh85106252.
|
| 650 |
|
0 |
|a Probabilities.
|0 http://id.loc.gov/authorities/subjects/sh85107090.
|
| 650 |
|
7 |
|a Artificial intelligence.
|2 fast
|0 (OCoLC)fst00817247.
|
| 650 |
|
7 |
|a Causation.
|2 fast
|0 (OCoLC)fst00849829.
|
| 650 |
|
7 |
|a Prediction (Logic)
|2 fast
|0 (OCoLC)fst01075024.
|
| 650 |
|
7 |
|a Probabilities.
|2 fast
|0 (OCoLC)fst01077737.
|
| 776 |
0 |
8 |
|i Print version:
|a Shafer, Glenn, 1946-
|t Art of causal conjecture.
|d Cambridge, Mass. : MIT Press, ©1996
|z 026219368X
|w (DLC) 96012572
|w (OCoLC)34411340.
|
| 856 |
4 |
0 |
|u https://colorado.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/1403.001.0001?locatt=mode:legacy
|z Full Text (via MIT Press)
|
| 830 |
|
0 |
|a Artificial intelligence (Cambridge, Mass.)
|0 http://id.loc.gov/authorities/names/n90648485.
|
| 907 |
|
|
|a .b120951071
|b 03-01-22
|c 02-14-22
|
| 915 |
|
|
|a -
|
| 998 |
|
|
|a web
|b 02-28-22
|c b
|d b
|e -
|f eng
|g mau
|h 4
|i 1
|
| 907 |
|
|
|a .b120951071
|b 02-28-22
|c 02-14-22
|
| 944 |
|
|
|a MARS - RDA ENRICHED
|
| 956 |
|
|
|a MIT Press Direct to Open Backfile
|
| 956 |
|
|
|b MIT Press Direct to Open Backfile Complete Monographs
|
| 999 |
f |
f |
|i 2eda8973-d8b4-55c3-bc18-855012c85440
|s 72a5726d-34bd-596d-aba4-1e8eb9b841ae
|
| 952 |
f |
f |
|p Can circulate
|a University of Colorado Boulder
|b Online
|c Online
|d Online
|e Q335 .S45 1996eb
|h Library of Congress classification
|i web
|n 1
|
