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170406  eng 
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a 9783319524016

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1 

a Carlton, Matthew A.

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0 
0 
a Probability with Applications in Engineering, Science, and Technology
h Elektronische Ressource
c by Matthew A. Carlton, Jay L. Devore

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a 2nd ed. 2017

260 


a Cham
b Springer International Publishing
c 2017, 2017

300 


a XXVI, 610 p. 209 illus., 178 illus. in color
b online resource

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0 

a Probability  Discrete Random Variables and Probability Distributions  Continuous Random Variables and Probability Distributions  Joint probability distributions and their applications  The Basics of Statistical Inference  Markov chains  Random processes  Introduction to signal processing

653 


a Statistical Theory and Methods

653 


a Statistics

653 


a Probability Theory

653 


a Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences

653 


a Probabilities

700 
1 

a Devore, Jay L.
e [author]

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0 
7 
a eng
2 ISO 6392

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b Springer
a Springer eBooks 2005

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0 

a Springer Texts in Statistics

028 
5 
0 
a 10.1007/9783319524016

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0 
u https://doi.org/10.1007/9783319524016?nosfx=y
x Verlag
3 Volltext

082 
0 

a 519.5

520 


a 5), Markov chains (Ch. 6), stochastic processes (Ch. 7), and signal processing (Ch. 8—available exclusively online and specifically designed for electrical and computer engineers, making the book suitable for a oneterm class on random signals and noise). For a yearlong course, core chapters (14) are accessible to those who have taken a year of univariate differential and integral calculus; matrix algebra, multivariate calculus, and engineering mathematics are needed for the latter, more advanced chapters. At the heart of the textbook’s pedagogy are 1,100 applied exercises, ranging from straightforward to reasonably challenging, roughly 700 exercises in the first four “core” chapters alone—a selfcontained textbook of problems introducing basic theoretical knowledge necessary for solving problems and illustrating how to solve the problems at hand – in R and MATLAB, including code so that students can create simulations.

520 


a New to this edition •Updated and reworked Recommended Coverage for instructors, detailing which courses should use the textbook and how to utilize different sections for various objectives and time constraints • Extended and revised instructions and solutions to problem sets • Overhaul of Section 7.7 on continuoustime Markov chains • Supplementary materials include three sample syllabi and updated solutions manuals for both instructors and students

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a This updated and revised firstcourse textbook in applied probability provides a contemporary and lively postcalculus introduction to the subject of probability. The exposition reflects a desirable balance between fundamental theory and many applications involving a broad range of real problem scenarios. It is intended to appeal to a wide audience, including mathematics and statistics majors, prospective engineers and scientists, and those business and social science majors interested in the quantitative aspects of their disciplines. The textbook contains enough material for a yearlong course, though many instructors will use it for a single term (one semester or one quarter). As such, three course syllabi with expanded course outlines are now available for download on the book’s page on the Springer website. A oneterm course would cover material in the core chapters (14), supplemented by selections from one or more of the remaining chapters on statistical inference (Ch.
