149,93 €
166,59 €
-10% with code: EXTRA
Bayes' Rule
Bayes' Rule
149,93
166,59 €
  • We will send in 10–14 business days.
Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and Python programs provided online. The tutorial style of writin…
  • Publisher:
  • ISBN-10: 0993367917
  • ISBN-13: 9780993367915
  • Format: 15.2 x 22.9 x 1.1 cm, hardcover
  • Language: English
  • SAVE -10% with code: EXTRA

Bayes' Rule (e-book) (used book) | James V Stone | bookbook.eu

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Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and Python programs provided online. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis.

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  • Author: James V Stone
  • Publisher:
  • ISBN-10: 0993367917
  • ISBN-13: 9780993367915
  • Format: 15.2 x 22.9 x 1.1 cm, hardcover
  • Language: English English

Discovered by an 18th century mathematician and preacher, Bayes' rule is a cornerstone of modern probability theory. In this richly illustrated book, a range of accessible examples is used to show how Bayes' rule is actually a natural consequence of common sense reasoning. Bayes' rule is then derived using intuitive graphical representations of probability, and Bayesian analysis is applied to parameter estimation using the MatLab and Python programs provided online. The tutorial style of writing, combined with a comprehensive glossary, makes this an ideal primer for novices who wish to become familiar with the basic principles of Bayesian analysis.

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