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Uncertainty The Soul of Modeling, Probability & Statistics

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This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance."



The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models.


Its jargon-free approach asserts that standard methods, such as out-of-the-box regression, cannot help in discovering cause. This new way of looking at uncertainty ties together disparate fields — probability, physics, biology, the “soft” sciences, computer science — because each aims at discovering cause (of effects). It broadens the understanding beyond frequentist and Bayesian methods to propose a Third Way of modeling.

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Detail Information

Series Title

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Call Number

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Publisher

: Springer Cham., 2016

Collation

23 b/w illustrations

Language

English

ISBN/ISSN

978-3-319-39756-6

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

online resource

Edition

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Subject(s)

Computer Science
Physics
Statistical Theory and Methods
Probability Theory
Statistics in Engineering
Chemistry and Earth Sciences
Philosophy of Mathematics
Epistemology, Logic

Specific Detail Info

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Statement of Responsibility

William Briggs

Other Information

Cataloger

Yudi

Source

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Validator

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