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Probability and simulation

Okten, Giray.

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Probability and simulation

Record Type:	Electronic resources : Monograph/item
Title/Author:	Probability and simulation/ by Giray Okten.
Author:	Okten, Giray.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	x, 152 p. :ill., digital ;24 cm.
[NT 15003449]:	Probability -- Discrete Random Variables -- Continuous Random Variables -- Markov Chains -- Brownian Motion -- Benford's Law -- Data for Project 12 -- Partial Solutions to Projects -- References.
Contained By:	Springer Nature eBook
Subject:	Probabilities. -
Online resource:	https://doi.org/10.1007/978-3-030-56070-6
ISBN:	9783030560706

Probability and simulation
Okten, Giray.

Probability and simulation[electronic resource] /by Giray Okten. - Cham :Springer International Publishing :2020. - x, 152 p. :ill., digital ;24 cm. - Springer undergraduate texts in mathematics and technology,1867-5506. - Springer undergraduate texts in mathematics and technology..

Probability -- Discrete Random Variables -- Continuous Random Variables -- Markov Chains -- Brownian Motion -- Benford's Law -- Data for Project 12 -- Partial Solutions to Projects -- References.

This undergraduate textbook presents an inquiry-based learning course in stochastic models and computing designed to serve as a first course in probability. Its modular structure complements a traditional lecture format, introducing new topics chapter by chapter with accompanying projects for group collaboration. The text addresses probability axioms leading to Bayes' theorem, discrete and continuous random variables, Markov chains, and Brownian motion, as well as applications including randomized algorithms, randomized surveys, Benford's law, and Monte Carlo methods. Adopting a unique application-driven approach to better study probability in action, the book emphasizes data, simulation, and games to strengthen reader insight and intuition while proving theorems. Additionally, the text incorporates codes and exercises in the Julia programming language to further promote a hands-on focus in modelling. Students should have prior knowledge of single variable calculus. Giray Ökten received his PhD from Claremont Graduate University. He has held academic positions at University of Alaska Fairbanks, Ball State University, and Florida State University. He received a Fulbright U.S. Scholar award in 2015. His research interests include Monte Carlo methods and computational finance.

ISBN: 9783030560706

Standard No.: 10.1007/978-3-030-56070-6doiSubjects--Topical Terms:

518889
Probabilities.

LC Class. No.: QA273 / .O58 2020

Dewey Class. No.: 519.2

Probability and simulation
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505 0 $a Probability -- Discrete Random Variables -- Continuous Random Variables -- Markov Chains -- Brownian Motion -- Benford's Law -- Data for Project 12 -- Partial Solutions to Projects -- References.
520 $a This undergraduate textbook presents an inquiry-based learning course in stochastic models and computing designed to serve as a first course in probability. Its modular structure complements a traditional lecture format, introducing new topics chapter by chapter with accompanying projects for group collaboration. The text addresses probability axioms leading to Bayes' theorem, discrete and continuous random variables, Markov chains, and Brownian motion, as well as applications including randomized algorithms, randomized surveys, Benford's law, and Monte Carlo methods. Adopting a unique application-driven approach to better study probability in action, the book emphasizes data, simulation, and games to strengthen reader insight and intuition while proving theorems. Additionally, the text incorporates codes and exercises in the Julia programming language to further promote a hands-on focus in modelling. Students should have prior knowledge of single variable calculus. Giray Ökten received his PhD from Claremont Graduate University. He has held academic positions at University of Alaska Fairbanks, Ball State University, and Florida State University. He received a Fulbright U.S. Scholar award in 2015. His research interests include Monte Carlo methods and computational finance.
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