Synopsis
This text stresses modern ideas, including simulation and interpretation of results. It focuses on the aspects of probability most relevant to applications, such as stochastic modeling, Markov chains, reliability, and queuing.
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About the Author
James J. Higgins is Professor of Statistics at Kansas State University and Fellow of the American Statistical Association. He is the co-author of the Duxbury textbook CONCEPTS IN PROBABILITY AND STOCHASTIC MODELING with Sallie Keller-McNulty and he is author of INTRODUCTION TO MODERN NONPARAMETRIC STATISTICS as well as having over 80 scientific publications to his credit. In addition, he is a statistical consultant for Kansas State Research and Extension. His research interests include nonparametric statistics and reliability theory.
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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Concepts in Probability and Stochastic Modeling (An Alexander Kugushev Book)
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