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Introduction to Probability with Statistical Applications

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  • 400pages
  • 14 heures de lecture

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Now in its second edition, this textbook introduces probability and statistics to non-mathematics majors who require a less detailed approach than comprehensive treatments. It covers the mathematical laws of random phenomena, including discrete and continuous random variables, expectation and variance, and key probability distributions like binomial, Poisson, and normal distributions. The new edition incorporates classical examples such as Montmort's problem, the ballot problem, and Bertrand’s paradox, along with applications like the Maxwell-Boltzmann and Bose-Einstein distributions in physics. Key features include 35 new exercises, an expanded section on set algebra, enhanced chapters on probabilities with more classical examples, a new section on regression, and an online instructors' manual with solutions to all exercises. This text is ideal for advanced undergraduate and graduate students in computer science, engineering, and other natural and social sciences who possess only a basic calculus background. The first edition was praised for its clarity and accessibility, making it suitable for students with limited mathematical expertise. Each concept is thoroughly explained, accompanied by detailed examples and well-articulated proofs.

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Introduction to Probability with Statistical Applications, Ge za Schay

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Année de publication
2018
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