Product Description: Peter Goos, Department of Statistics, University of Leuven, Faculty of Bio-Science Engineering and University of Antwerp, Faculty of Applied Economics, BelgiumDavid Meintrup, Department of Mathematics and Statistics, University of Applied Sciences Ingolstadt, Faculty of Mechanical Engineering, GermanyThorough presentation of introductory statistics and probability theory, with numerous examples and applications using JMPJMP: Graphs, Descriptive Statistics and Probability provides an accessible and thorough overview of the most important descriptive statistics for nominal, ordinal and quantitative data with particular attention to graphical representations...read more

Product Description: Stated Preference Methods Using R explains how to use stated preference (SP) methods, which are a family of survey methods, to measure people’s preferences based on decision making in hypothetical choice situations. Along with giving introductory explanations of the methods, the book collates information on existing R functions and packages as well as those prepared by the authors...read more

Product Description: Cohesively Incorporates Statistical Theory with R Implementation Since the publication of the popular first edition of this comprehensive textbook, the contributed R packages on CRAN have increased from around 1,000 to over 6,000...read more

Product Description: Practical Statistical Methods: A SAS Programming Approach presents a broad spectrum of statistical methods useful for researchers without an extensive statistical background. In addition to nonparametric methods, it covers methods for discrete and continuous data...read more

Product Description: Introduction to Probability with Mathematica 2ND EDITION by Kevin J. Hastings. CRC Press I, LLC,2010 (

Product Description: Designed for an intermediate undergraduate course, Probability and Statistics with R shows students how to solve various statistical problems using both parametric and nonparametric techniques via the open source software R. It provides numerous real-world examples, carefully explained proofs, end-of-chapter problems, and illuminating graphs to facilitate hands-on learning...read more

Probability is a vital measure in numerous disciplines, from bioinformatics and econometrics to finance/insurance and computer science. Developed from a successful course, Fundamental Probability provides an engaging and hands-on introduction to this important topic. Whilst the theory is explored in detail, this book also emphasises practical applications, with the presentation of a large variety of examples and exercises, along with generous use of computational tools. Based on international teaching experience with students of statistics, mathematics, finance and econometrics, the book: Presents new, innovative material alongside the classic theory. Goes beyond standard presentations by carefully introducing and discussing more complex subject matter, including a richer use of combinatorics, runs and occupancy distributions, various multivariate sampling schemes, fat-tailed distributions, and several basic concepts used in finance. Emphasises computational matters and programming methods via generous use of examples in MATLAB. Includes a large, self-contained Calculus/Analysis appendix with derivations of all required tools, such as Leibniz’ rule, exchange of derivative and integral, Fubini’s theorem, and univariate and multivariate Taylor series. Presents over 150 end-of-chapter exercises, graded in terms of their difficulty, and accompanied by a full set of solutions online. This book is intended as an introduction to the theory of probability for students in biology, mathematics, statistics, economics, engineering, finance, and computer science who possess the prerequisite knowledge of basic calculus and linear algebra.

Product Description: "Global Marketing Strategies" earns high praise for its up-to-date coverage of the field, especially from instructors of graduate-level courses. In addition to the latest research, this text reinforces the importance of global strategic thinking, or the "global mindset," with current examples from well-known companies across Europe, Asia, and Africa, as well as both North and South America...read more

Product Description: An accessible introduction to probability, stochastic processes, and statistics for computer science and engineering applicationsThis updated and revised edition of the popular classic relates fundamental concepts in probability and statistics to the computer sciences and engineering...read more (view table of contents, read Amazon.com's description)

Great advances have been made in recent years in the field of computational probability. In particular, the state of the art - as it relates to queuing systems, stochastic Petri-nets and systems dealing with reliability - has benefited significantly from these advances. The objective of this book is to make these topics accessible to researchers, graduate students, and practitioners. Great care was taken to make the exposition as clear as possible. Every line in the book has been evaluated, and changes have been made whenever it was felt that the initial exposition was not clear enough for the intended readership. The work of major research scholars in this field comprises the individual chapters of Computational Probability. The first chapter describes, in nonmathematical terms, the challenges in computational probability. Chapter 2 describes the methodologies available for obtaining the transition matrices for Markov chains, with particular emphasis on stochastic Petri-nets. Chapter 3 discusses how to find transient probabilities and transient rewards for these Markov chains. The next two chapters indicate how to find steady-state probabilities for Markov chains with a finite number of states. Both direct and iterative methods are described in Chapter 4. Details of these methods are given in Chapter 5. Chapters 6 and 7 deal with infinite-state Markov chains, which occur frequently in queueing, because there are times one does not want to set a bound for all queues. Chapter 8 deals with transforms, in particular Laplace transforms. The work of Ward Whitt and his collaborators, who have recently developed a number of numerical methods for Laplace transform inversions, is emphasized in this chapter. Finally, if one wants to optimize a system, one way to do the optimization is through Markov decision making, described in Chapter 9. Markov modeling has found applications in many areas, three of which are described in detail: Chapter 10 analyzes discrete-time queues, Chapter 11 describes networks of queues, and Chapter 12 deals with reliability theory. (view table of contents)

Product Description: This textbook aims to provide comprehensive coverage of probability and random processes using the simulation software MATLAB. Explanations of probability and estimation are directed at the student for whom prior exposure to concepts of probability is minimal...read more (view table of contents, read Amazon.com's description)

Product Description: Probability theory is fundamental to the teaching and understanding of statistics. This book is dedicated to applying these laws in a variety of applications resulting in the formulation of the more common probability distributions.

Product Description: MATLAB-based procedures and functions carrying out computations in basic probability is contained in this pack of book and accompanying disk. A compatible disk contains M-files with scripts for the functions and procedures employed and relevant data for some of the problems and solutions to the reinforcement problems...read more