Conclusions From a Study of Decision Making
Conclusions From a Study of Decision Making
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In our eReader you can find the full English version of the book. Read Conclusions From a Study of Decision Making Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Conclusions From a Study of Decision Making
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Probability ' Mathematical probability theory, either of the Neyman-Pearson or Baysean variety, seems quite unsuited as a source of concepts for describing how Dms code and operate with perceived Uncertainty, even in the limited context "perceived inability to predict exactly the consequence which would flow from choice of a given alternative". These are the more obvious reasons: i_. Additivity, i. E the distributive property that all Dms' Probability Uncertainty indices must add up to "one", o...r Certainty, over the set of all possible and mutually exclusive consequences of any given alternative > is a computational constraint that Dms do not generally seem to (have learned to) ■ ^pply in their own estiuiation of Uncertainty "indices".
; Shackle invented his non-additive Potential Surprise concept to cope with this objection to formal Probability theory* Unfortunately the compu- tational assumptions that Shackle sees fit to impose on his Potential- Surprise calculating Dms are so severe that not much empirically descriptive reasonable- ness seems to remain by the time Shackle has finished putting all his sugges- tions together into a complete theory.
What to read after Conclusions From a Study of Decision Making?
You can find similar books in the "Read Also" column, or choose other free books by Peer Peer Olav Soelberg to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
Probability ' Mathematical probability theory, either of the Neyman-Pearson or Baysean variety, seems quite unsuited as a source of concepts for describing how Dms code and operate with perceived Uncertainty, even in the limited context "perceived inability to predict exactly the consequence which would flow from choice of a given alternative". These are the more obvious reasons: i_. Additivity, i. E the distributive property that all Dms' Probability Uncertainty indices must add up to "one", o...r Certainty, over the set of all possible and mutually exclusive consequences of any given alternative > is a computational constraint that Dms do not generally seem to (have learned to) ■ ^pply in their own estiuiation of Uncertainty "indices".
; Shackle invented his non-additive Potential Surprise concept to cope with this objection to formal Probability theory* Unfortunately the compu- tational assumptions that Shackle sees fit to impose on his Potential- Surprise calculating Dms are so severe that not much empirically descriptive reasonable- ness seems to remain by the time Shackle has finished putting all his sugges- tions together into a complete theory.
What to read after Conclusions From a Study of Decision Making?
You can find similar books in the "Read Also" column, or choose other free books by Peer Peer Olav Soelberg to read onlineMoreLess
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