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Probability theory and examples / Claire Montemar.

By: Montemar, Claire, authorMaterial type: TextTextPublisher: Oakville, ON : Arcler Press, c2018Description: ix, 343 pagesISBN: 9781984601865 (e-book)Subject(s): Probability theory and examples -- ProbabilitiesLOC classification: EBOP QA 273 | M66 2018Online resources: Electronic Resources https://www.bibliotex.com/pdfreader/probability-theory-examples50101690 https://www.bibliotex.com/pdfreader/probability-theory-examples50101690
Contents:
Chapter 1: History and Fundamentals of Probability Chapter 2: Axioms of Probability Chapter 3: Random Variable Chapter 4: Expectation Chapter 5: Discrete Probability Distribution - I Chapter 6: Discrete Probability Distribution - II Chapter 7: Continuous Probability Distributions Chapter 8: Normal Distribution Chapter 9: Regression and Correlation
Summary: Presenting a clear, comprehensive and systematic account of various probability theories and to explain how they relate to one another. This text is written for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science. Well known for the clear, inductive nature of its exposition, this book is an excellent introduction to mathematical probability theory with examples.
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Item type Current location Collection Shelving location Call number Copy number Status Date due Barcode
E-Books E-Books Cavite State University - CCAT Campus
Electronic Resources ER EBOP QA 273 M66 2018 (Browse shelf) 1 copy Available EBOP0000053

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Includes bibliographical references and index.

Chapter 1: History and Fundamentals of Probability
Chapter 2: Axioms of Probability
Chapter 3: Random Variable
Chapter 4: Expectation
Chapter 5: Discrete Probability Distribution - I
Chapter 6: Discrete Probability Distribution - II
Chapter 7: Continuous Probability Distributions
Chapter 8: Normal Distribution
Chapter 9: Regression and Correlation

Presenting a clear, comprehensive and systematic account of various probability theories and to explain how they relate to one another. This text is written for an introductory probability course at the university level for undergraduates in mathematics, the physical and social sciences, engineering, and computer science. Well known for the clear, inductive nature of its exposition, this book is an excellent introduction to mathematical probability theory with examples.

In English text.

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