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Uncertainty - The Soul of Modeling, Probability & Statistics (Hardcover, 1st ed. 2016)
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Uncertainty - The Soul of Modeling, Probability & Statistics (Hardcover, 1st ed. 2016)
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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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