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Book
xv, 767 pages ; 24 cm
Sheldon Ross's classic bestseller, Introduction to Probability Models, has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied fields such as engineering, computer science, management science, the physical and social sciences, and operations research. The hallmark features of this renowned text remain in this eleventh edition: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topic; and real-world applications in engineering, science, business and economics. The 65% new chapter material includes coverage of finite capacity queues, insurance risk models, and Markov chains, as well as updated data. * Updated data, and a list of commonly used notations and equations, instructor's solutions manual* Offers new applications of probability models in biology and new material on Point Processes, including the Hawkes process* Introduces elementary probability theory and stochastic processes, and shows how probability theory can be applied in fields such as engineering, computer science, management science, the physical and social sciences, and operations research* Covers finite capacity queues, insurance risk models, and Markov chains * Contains compulsory material for new Exam 3 of the Society of Actuaries including several sections in the new exams* Appropriate for a full year course, this book is written under the assumption that students are familiar with calculus.
(source: Nielsen Book Data)9780124079489 20160612
Engineering Library (Terman), eReserve
MS&E-223-01

2. Simulation [2013]

Book
1 online resource (xii, 310 pages) : illustrations
  • Elements of probability
  • Random numbers
  • Generating discrete random variables
  • Generating continuous random variables
  • The multivariate normal distribution and copulas
  • The discrete event simulation approach
  • Statistical analysis of simulated data
  • Variance reduction techniques
  • Additional variance reduction techniques
  • Statistical validation techniques
  • Markov chain Monte Carlo methods.
The 5th edition of Ross's Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This latest edition features all-new material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis. Additionally, the 5th edition expands on Markov chain monte carlo methods, and offers unique information on the alias method for generating discrete random variables. By explaining how a computer can be used to generate random numbers and how to use these random numbers to generate the behavior of a stochastic model over time, Ross's Simulation, 5th edition presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model. * Additional material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis* Additional material and examples on Markov chain Monte Carlo methods* Unique material on the alias method for generating discrete random variables* Additional material on generating multivariate normal vectors.
(source: Nielsen Book Data)9780124158252 20161114
eReserve
MS&E-223-01
Book
1 online resource.
The 5th edition of Ross's Simulation continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and interpret real phenomena. Readers learn to apply results of these analyses to problems in a wide variety of fields to obtain effective, accurate solutions and make predictions about future outcomes. This latest edition features all-new material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis. Additionally, the 5th edition expands on Markov chain monte carlo methods, and offers unique information on the alias method for generating discrete random variables. By explaining how a computer can be used to generate random numbers and how to use these random numbers to generate the behavior of a stochastic model over time, Ross's Simulation, 5th edition presents the statistics needed to analyze simulated data as well as that needed for validating the simulation model. * Additional material on variance reduction, including control variables and their use in estimating the expected return at blackjack and their relation to regression analysis* Additional material and examples on Markov chain Monte Carlo methods* Unique material on the alias method for generating discrete random variables* Additional material on generating multivariate normal vectors.
(source: Nielsen Book Data)9780124158252 20161114
eReserve
MS&E-223-01
Book
xviii, 776 pages : illustrations ; 24 cm.
  • 1 Basic Simulation Modeling 2 Modeling Complex Systems 3 Simulation Software 4 Review of Basic Probability and Statistics 5 Building Valid, Credible, and Appropriately Detailed Simulation Models 6 Selecting Input Probability Distributions 7 Random-Number Generators 8 Generating Random Variates 9 Output Data Analysis for a Single System 10 Comparing Alternative System Configurations 11 Variance-Reduction Techniques 12 Experimental Design, Sensitivity Analysis, and Optimization 13 Simulation of Manufacturing Systems.
  • (source: Nielsen Book Data)9780073401324 20160612
Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self-study. The book is widely regarded as the "bible" of simulation and now has more than 155,000 copies in print and has been cited more than 14,000 times. The book can serve as the primary text for a variety of courses; for example: a first course in simulation at the junior, senior, or beginning-graduate-student level in Engineering, Manufacturing, Business, or Computer Science. At the end of such a course, the students will be prepared to carry out complete and correct simulation studies, and to take Advanced Simulation courses; a second course in simulation for graduate students in any of the above disciplines; after completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research; and, an introduction to simulation as part of a general course in Operations Research or Management Science.
(source: Nielsen Book Data)9780073401324 20160612
Engineering Library (Terman)
MS&E-223-01
Book
xv, 784 p. : ill. ; 24 cm.
Ross' classic bestseller, "Introduction to Probability Models", has been used extensively by professionals and as the primary text for a first undergraduate course in applied probability. It provides an introduction to elementary probability theory and stochastic processes, and shows how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. With the addition of several new sections relating to actuaries, this text is highly recommended by the Society of Actuaries. New to this Edition are 65 per cent new chapter material including coverage of finite capacity queues, insurance risk models and Markov chains. It contains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new exams. It has updated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, test bank, and companion website. it includes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field. Hallmark features: superior writing style; excellent exercises and examples covering the wide breadth of coverage of probability topics; and real-world applications in engineering, science, business and economics.
(source: Nielsen Book Data)9780123756862 20160528
Engineering Library (Terman)
MS&E-223-01
Book
xxi, 818 p. : ill. ; 25 cm.
In this 3rd edition revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. Concepts are motivated, illustrated and explained in a way that attempts to increase one's intuition. To quote from the preface, 'It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data'. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud and many others. Ancillary list includes: Instructor's Manual; Student Solutions Manual; Student Solutions Manual for 2nd Edition; Sample Chapter, eBook; and, Companion Website w/Data Sets. This title features unique historical perspective profiling prominent statisticians and historical events to motivate learning by providing interest and context. Use of exercises and examples helps guide the student towards independent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud. Summary/Key Terms - chapters end with detailed reviews of important concepts and formulas, key terms and definitions which are useful to students as study tools. Data sets from text and exercise material will be available to download from the text website, saves students time.
(source: Nielsen Book Data)9780123743886 20160615
Engineering Library (Terman)
MS&E-223-01
Book
xix, 768 p. : ill. ; 24 cm. + 1 CD-ROM (4 3/4 in.)
  • 1. Basic Simulation Modeling 2. Modeling Complex Systems 3. Simulation Software 4. Review of Basic Probability and Statistics 5. Building Valid, Credible, and Appropriately Detailed Simulation Models 6. Selecting Input Probability Distributions 7. Random-Number Generators 8. Generating Random Variates 9. Output Data Analysis for a Single System 10. Comparing Alternative System Configurations 11. Variance-Reduction Techniques 12. Experimental Design and Optimization 13. Simulation of Manufacturing Systems.
  • (source: Nielsen Book Data)9780072988437 20160527
Since the publication of the first edition in 1982, the goal of "Simulation Modeling and Analysis" has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the "bible" of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: a first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses; and a second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. It provides an introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).
(source: Nielsen Book Data)9780072988437 20160527
Engineering Library (Terman)
MS&E-223-01
Book
xvii, 809 p. : ill. (some col.) ; 25 cm. + 1 CD-ROM (4 3/4 in.)
  • Preface Introduction to Statistics Describing Data Sets Using Statistics to Summarize Data Sets Probability Discrete Random Variables Normal Random Variables Distributions of Sampling Statistics Estimation Testing Statistical Hypotheses Hypothesis Tests Concerning Two Populations Analysis of Variance Linear Regression Chi-Squared Goodness of Fit Tests Nonparametric Hypotheses Tests Quality Control Appendices.
  • (source: Nielsen Book Data)9780125971324 20160528
In this revised text, master expositor Sheldon Ross has produced a unique work in introductory statistics. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, and an explanation of intuition and ideas behind the statistical methods. To quote from the preface, 'It is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data'. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions and examples. Ross' clear writing style leads students easily through descriptive and inferential statistics. This book features: hundreds of exercises assess students' conceptual and computational understanding; real data sets from current issues draw from a variety of disciplines; Statistics in Perspective that demonstrate real-world application of techniques and concepts; Historical Perspectives sections that profile prominent statisticians and events; and, Chapter Introductions that pose realistic statistical situations. This book features Chapter Summaries and Key Terms that reinforce learning. There is a detachable Formula Card that includes frequently used tables and formulas to facilitate studying. An enclosed CD-ROM contains programs that can be used to solve basic computation problems. New in this Edition are dozens of new and updated examples and exercises. New sections on: assessing the linear regression model by analyzing residuals; quality control; counting principles; Poisson random variables. There are detailed edits and enhancements based on users' feedback. A computerized test bank, plus updates to other ancillaries Ancillaries: Instructor's Manual; "Student Solutions Manual" (ISBN: 0120885514); Printed Test Bank; Computerized Test Bank; and, Instructor's web site with additional online materials.
(source: Nielsen Book Data)9780125971324 20160528
Engineering Library (Terman), SAL1&2 (on-campus shelving)
MS&E-223-01
Book
xxii, 509 p. : ill. ; 24 cm.
  • Introduction * Modelling with Stochastic Petri Nets * The Marking Process * Modelling Power * Recurrence * Regenerative Simulation * Alternative Simulation Methods * Delays * Colored Stochastic Petri Nets * Appendix A Selected Background * References * Index.
  • (source: Nielsen Book Data)9780387954455 20160528
This book is about stochastic Petri nets (SPNs), which have proven to be a popular tool for modelling and performance analysis of complex discrete-event stochastic systems. The focus is on methods for modelling a system as an SPN with general firing times and for studying the long-run behavior of the resulting SPN model using computer simulation. Modelling techniques are illustrated in the context of computer, manufacturing, telecommunication, workflow, and transportation systems. The simulation discussion centers on the theory that underlies estimation procedures such as the regenerative method, the method of batch means, and spectral methods. Tying these topics together are conditions on the building blocks of an SPN under which the net is stable over time and specified estimation procedures are valid. In addition, the book develops techniques for comparing the modelling power of different discrete-event formalisms. These techniques provide a means for making principled choices between alternative modelling frameworks and also can be used to extend stability results and limit theorems from one framework to another. As an overview of fundamental modelling, stability, convergence, and estimation issues for discrete-event systems, this book will be of interest to researchers and graduate students in Applied Mathematics, Operations Research, Applied Probability, and Statistics. This book also will be of interest to practitioners of Industrial, Computer, Transportation, and Electrical Engineering, because it provides an introduction to a powerful set of tools both for modelling and for simulation-based performance analysis. Peter J. Haas is a member of the Research Staff at the IBM Almaden Research Center in San Jose, California. He also teaches Computer Simulation at Stanford University and is an Associate Editor (Simulation Area) for Operations Research.
(source: Nielsen Book Data)9780387954455 20160528
Engineering Library (Terman), eReserve
MS&E-223-01
Book
x, 203 p. 25 cm.
Engineering Library (Terman)
MS&E-223-01
Engineering Library (Terman)
MS&E-223-01