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Uncertainty
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Uncertainty : The Soul of Modeling, Probability & Statistics

Softcover reprint of the original 1st ed. 2016

Book Details

Format Paperback / Softback
ISBN-10 3319819585
ISBN-13 9783319819587
Edition Softcover reprint of the original 1st ed. 2016
Publisher Springer International Publishing AG
Imprint Springer International Publishing AG
Country of Manufacture GB
Country of Publication GB
Publication Date May 30th, 2018
Print length 258 Pages
Weight 434 grams
Dimensions 15.50 x 23.50 x 1.70 cms
Ksh 16,200.00
Werezi Extended Catalogue 0 in stock

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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.
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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