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<P><EM>Practical Business Statistics, Eighth Edition,</EM> offers readers a practical, accessible approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book fosters deep understanding of ...
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<EM>Sabermetrics: Baseball, Steroids, and How the Game has Changed Over the Past Two Generations</EM> offers an introduction to this increasing area of interest to statisticians, students of the game, and many others. Pairing a primer on the applied ...
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<EM>Introduction to Robust Estimating and Hypothesis Testing, Fifth Edition</EM> is a useful ‘howto’ on the application of robust methods utilizing easytouse software. This trusted resource provides an overview of modern robust methods, including ...
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<P><EM>Quantitative Analysis and Modeling of Earth and Environmental Data: SpaceTime and Spacetime Data Considerations</EM> introduces the notion of chronotopologic data analysis that offers a systematic, quantitative analysis of multisourced data ...
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<EM>Statistical Methods, Fourth Edition, </EM>is designed to introduce students to a widerange of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate...
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<P><EM>Mathematica by Example, Sixth Edition</EM> is an essential resource for the Mathematica user, providing stepbystep instructions on achieving results from this powerful software tool. The book fully accounts for the changes to functionality a...
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<P><EM>Introduction to Chemical Engineering Analysis Using Mathematica, Second Edition</EM> reviews the processes and designs used to manufacture, use, and dispose of chemical products using Mathematica, one of the most powerful mathematical software...
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<EM>Advanced Mathematics for Engineering Students: The Essential Toolbox</EM> provides a concise treatment for applied mathematics. Derived from two semester advanced mathematics courses at the author’s university, the book delivers the mathematical ...
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<P><EM>Basic Statistics with R: Reaching Decisions with Data</EM> provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summar...
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<EM>Python Programming and Numerical Methods: A Guide for Engineers and Scientists</EM> introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational proble...
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<P><EM>Introduction to Probability and Statistics for Engineers and Scientists, Sixth Edition, </EM>uniquely emphasizes how probability informs statistical problems, thus helping readers develop an intuitive understanding of the statistical procedure...
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<P><EM>Calculus for Engineering Students: Fundamentals, Real Problems, and Computers</EM> insists that mathematics cannot be separated from chemistry, mechanics, electricity, electronics, automation, and other disciplines. It emphasizes interdiscipli...
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<P><EM>Mathematical Statistics with Applications in R, Third Edition,</EM> offers a modern calculusbased theoretical introduction to mathematical statistics and applications. The book covers many modern statistical computational and simulation conce...
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<P>Providing an alternative to engineeringfocused resources in the area, <I>Programming Mathematics Using MATLAB® </I>introduces the basics of programming and of using MATLAB® by highlighting many mathematical examples. Emphasizing mathematical conc...
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<P><EM>A Modern Introduction to Differential Equations, Third Edition, </EM>provides an introduction to the basic concepts of differential equations. The book begins by introducing the basic concepts of differential equations, focusing on the analyti...
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<P><EM>Matrix Methods: Applied Linear Algebra and Sabermetrics, Fourth Edition,</EM> provides a unique and comprehensive balance between the theory and computation of matrices. Rapid changes in technology have made this valuable overview on the appli...
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<P><EM>Liengme’s Guide to Excel 2016 for Scientists and Engineers</EM> is a completely updated guide for students, scientists, and engineers who want to use Microsoft Excel 2016 to its full potential, whether you’re using a PC or a Mac. Electronic sp...
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<P><EM>Introduction to Algorithms for Data Mining and Machine Learning </EM>introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematic...
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<P><EM>GIS and Geostatistical Techniques for Groundwater Science</EM> provides a detailed synthesis of the application of GIS and geostatistics in groundwater studies. As the book illustrates, GIS can be a powerful tool for developing solutions for w...
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<P><EM>Statistics for Biomedical Engineers and Scientists: How to Analyze and Visualize Data</EM> provides an intuitive understanding of the concepts of basic statistics, with a focus on solving biomedical problems. Readers will learn how to understa...
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<P><EM>Introduction to Probability Models, Twelfth Edition,</EM> is the latest version of Sheldon Ross's classic bestseller. This trusted book introduces the reader to elementary probability modelling and stochastic processes and shows how probabilit...
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<P><EM>Model Engineering for Simulation</EM> provides a systematic introduction to the implementation of generic, normalized and quantifiable modeling and simulation using DEVS formalism. It describes key technologies relating to model lifecycle mana...
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<P><EM>Spatial Modeling in GIS and R for Earth and Environmental Sciences </EM>offers an integrated approach to spatial modelling using both GIS and R. Given the importance of Geographical Information Systems and geostatistics across a variety of app...
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<P>The fourth edition of <I>Numerical Methods Using MATLAB</I>® provides a clear and rigorous introduction to a wide range of numerical methods that have practical applications. The authors’ approach is to integrate MATLAB® with numerical analysis in...
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<P><EM>Algebraic and Combinatorial Computational Biology</EM> introduces students and researchers to a panorama of powerful and current methods for mathematical problemsolving in modern computational biology. Presented in a modular format, each topi...
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<P><EM>MATLAB: A Practical Introduction to Programming and Problem Solving</EM>, winner of TAA’s 2017 Textbook Excellence Award ("Texty"), guides the reader through both programming and builtin functions to easily exploit MATLAB's extensive capabili...
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<P><EM>Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations, Third Edition,</EM> continues the legacy of this authoritative and complete theoretical work. It is ideal for graduate and PhD students and wor...
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<P><EM>MolecularGenetic and Statistical Techniques for Behavioral and Neural Research</EM> presents the most exciting molecular and recombinant DNA techniques used in the analysis of brain function and behavior, a critical piece of the puzzle for cl...
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<P><EM>Introductory Differential Equations, Fifth Edition</EM> provides accessible explanations and new, robust sample problems. This valuable resource is appropriate for a first semester course in introductory ordinary differential equations (includ...
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<P><EM>Mathematical Physics with Partial Differential Equations, Second Edition,</EM> is designed for upper division undergraduate and beginning graduate students taking mathematical physics taught out by math departments. The new edition is based on...
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<P><EM>A Contemporary Study of Iterative Methods: Convergence, Dynamics and Applications</EM> evaluates and compares advances in iterative techniques, also discussing their numerous applications in applied mathematics, engineering, mathematical econo...
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<P><EM>Finite Element Analysis Applications: A Systematic and Practical Approach</EM> strikes a solid balance between more traditional FEA textbooks that focus primarily on theory, and the software specific guidebooks that help teach students and pro...
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<P><EM>Machine Learning: A ConstraintBased Approach</EM> provides readers with a refreshing look at the basic models and algorithms of machine learning, with an emphasis on current topics of interest that includes neural networks and kernel machines...
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<P><EM>Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence, Second Edition, </EM>provides a synthesis of modelbased approaches for analyzing presenceabsence data, allowing for imperfect detection. Beginning from...
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<P><EM>Handbook of Statistical Analysis and Data Mining Applications, Second Edition,</EM> is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all ...
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<P><EM>The Finite Element Method in Engineering, Sixth Edition,</EM> provides a thorough grounding in the mathematical principles behind the Finite Element Analysis technique—an analytical engineering tool originated in the 1960's by the aerospace an...
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<P><EM>Mathematica by Example, Fifth Edition</EM> is an essential desk reference for the beginning Mathematica user, providing stepbystep instructions on achieving results from this powerful software tool. The book fully accounts for the dramatic c...
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<P><EM>Mathematics for Neuroscientists, Second Edition, </EM>presents a comprehensive introduction to mathematical and computational methods used in neuroscience to describe and model neural components of the brain from ion channels to single neurons...
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<P><EM>Introductory Statistics, Fourth Edition, </EM>reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedur...
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<P><EM>Introduction to Robust Estimating and Hypothesis Testing, 4th Editon,</EM> is a ‘howto’ on the application of robust methods using available software. Modern robust methods provide improved techniques for dealing with outliers, skewed di...
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<P><EM>Practical Business Statistics, Seventh Edition</EM>, provides a conceptual, realistic, and matteroffact approach to managerial statistics that carefully maintains, but does not overemphasize mathematical correctness. The book provides deep u...
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<P><EM>Theory and Methods of Statistics</EM> covers essential topics for advanced graduate students and professional research statisticians. This comprehensive resource covers many important areas in one manageable volume, including core subjects suc...
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<P><EM>An Introduction to the Mathematics of Finance: A Deterministic Approach, Second edition,</EM> offers a highly illustrated introduction to mathematical finance, with a special emphasis on interest rates. This revision of the McCutcheonScott&nb...
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<P>Elementary Linear Algebra, 5<SUP>th</SUP> edition, by Stephen Andrilli and David Hecker, is a textbook for a beginning course in linear algebra for sophomore or junior mathematics majors. This text provides a solid introduction to both the computa...
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<P><EM>Numerical Methods for Partial Differential Equations: Finite Difference and Finite Volume Methods</EM> focuses on two popular deterministic methods for solving partial differential equations (PDEs), namely finite difference and finite volume m...
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<P><EM>Fundamentals of Technical Mathematics</EM> introduces key, applied mathematics for engineering technologists and technicians. Through a simple, engaging approach, the book reviews basic mathematics, including whole numbers, fractions, mixed nu...
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<P><EM>Risk Neutral Pricing and Financial Mathematics: A Primer</EM> provides a foundation to financial mathematics for those whose undergraduate quantitative preparation does not extend beyond calculus, statistics, and linear math. It covers a broad...
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<EM>Essential Statistics, Regression, and Econometrics, Second Edition,</EM> is innovative in its focus on preparing students for regression/econometrics, and in its extended emphasis on statistical reasoning, real data, pitfalls in data analysis, an...
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<P>This selfcontained module for independent study covers the subjects most often needed by nonmathematics graduates, such as fundamental calculus, linear algebra, probability, and basic numerical methods. The easilyunderstandable text of <EM>Intr...
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<P>Written by experts in both mathematics and biology, <EM>Algebraic and Discrete Mathematical Methods for Modern Biology</EM> offers a bridge between math and biology, providing a framework for simulating, analyzing, predicting, and modulating the b...
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<P>Completely updated guide for students, scientists and engineers who want to use Microsoft Excel 2013 to its full potential. Electronic spreadsheet analysis has become part of the everyday work of researchers in all areas of engineering and science...
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<P>Bioinspired computation, especially those based on swarm intelligence, has become increasingly popular in the last decade. <I>BioInspired Computation in Telecommunications </I>reviews the latest developments in bioinspired computation from both...
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<P><EM>Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis</EM>, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than bei...
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<P><EM>Principles of Financial Engineering, Third Edition,</EM> is a highly acclaimed text on the fastpaced and complex subject of financial engineering. This updated edition describes the "engineering" elements of financial engineering instead of t...
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<P><EM>Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition</EM> provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are stepbystep inst...
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<P><EM>An Introduction to Probability and Statistical Inference, Second Edition,</EM> guides you through probability models and statistical methods and helps you to think critically about various concepts. Written by awardwinning author George Rouss...
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<P>The eighth edition of the classic Gradshteyn and Ryzhik is an updated completely revised edition of what is acknowledged universally by mathematical and applied science users as the key reference work concerning the integrals and special functions...
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<P><EM>Numerical Linear Algebra with Applications</EM> is designed for those who want to gain a practical knowledge of modern computational techniques for the numerical solution of linear algebra problems, using MATLAB as the vehicle for computation....
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<P>The longawaited revision of <EM>Fundamentals of Applied Probability and Random Processes</EM> expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling ...
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<P>Most approaches to crime analysis focus on geographical crime mapping, which is helpful in identifying crime clusters and allocating police resources, but does not explain why a particular crime took place. <I>Applied Crime Analysis </I>presents a...
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<P><EM>Mathematics for Physical Science and Engineering</EM> is a complete text in mathematics for physical science that includes the use of symbolic computation to illustrate the mathematical concepts and enable the solution of a broader range of pr...
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Assuming no prior background in linear algebra or real analysis, <EM>An Introduction to MATLAB</EM>®<EM> Programming and Numerical Methods for Engineers</EM> enables you to develop good computational problem solving techniques through the use of nume...
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<P><EM>An Introduction to MeasureTheoretic Probability, Second Edition</EM>, employs a classical approach to teaching the basics of measure theoretic probability. This book provides in a concise, yet detailed way, the bulk of the probabilistic tools...
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<P><EM>An Introduction to the Mathematics of Financial Derivatives </EM>is a popular, intuitive text that eases the transition between basic summaries of financial engineering to more advanced treatments using stochastic calculus. Requiring only a ba...
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<P><EM>Introduction to Probability, Second Edition</EM>, discusses probability theory in a mathematically rigorous, yet accessible way. This onesemester basic probability textbook explains important concepts of probability while providing useful exe...
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<P>In this appealing and wellwritten text, Richard Bronson starts with the concrete and computational, and leads the reader to a choice of major applications. The first three chapters address the basics: matrices, vector spaces, and linear tran...
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<P>The new edition of <EM>Mathematical Modeling</EM>, the survey text of choice for mathematical modeling courses, adds ample instructor support and online delivery for solutions manuals and software ancillaries. </P>
<P>From genetic engineering to h...
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<P>The 5<SUP>th</SUP> edition of Ross’s <I>Simulation</I> continues to introduce aspiring and practicing actuaries, engineers, computer scientists and others to the practical aspects of constructing computerized simulation studies to analyze and inte...
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<P>Hirsch, Devaney, and Smale’s classic <EM>Differential Equations, Dynamical Systems, and an Introduction to Chaos</EM> has been used by professors as the primary text for undergraduate and graduate level courses covering differential equations...
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<P><EM>Statistics for Physical Sciences</EM> is an informal, relatively short, but systematic, guide to the more commonly used ideas and techniques in statistical analysis, as used in physical sciences, together with explanations of their origin...
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<P>The second edition of <EM>A Course in Real Analysis</EM> provides a solid foundation of real analysis concepts and principles, presenting a broad range of topics in a clear and concise manner. The book is excellent at balancing theory and applicat...
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<P><EM>Probability and Random Processes, Second Edition</EM> presents pertinent applications to signal processing and communications, two areas of key interest to students and professionals in today's booming communications industry. The book include...
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<EM>The Nuts and Bolts of Proofs: An Introduction to Mathematical Proofs</EM> provides basic logic of mathematical proofs and shows how mathematical proofs work. It offers techniques for both reading and writing proofs. The second chapter of the book...
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<P><EM>Strategy and Statistics in Clinical Trials</EM> deals with the research processes and the role of statistics in these processes. The book offers reallife case studies and provides a practical, how to guide to biomedical R&D. It describes ...
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<P>Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who want...
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<P>Serving as the foundation for a onesemester course in stochastic processes for students familiar with elementary probability theory and calculus, <EM>Introduction to Stochastic Modeling, Fourth Edition,</EM> bridges the gap between basic probabil...
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<P><EM>Computability Theory: An Introduction to Recursion Theory </EM>provides a concise, comprehensive, and authoritative introduction to contemporary computability theory, techniques, and results. The basic concepts and techniques of computability ...
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<P><EM>Statistical Methods, Third Edition,</EM> provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes...
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<P><EM>Advanced Calculus</EM> explores the theory of calculus and highlights the connections between calculus and real analysis  providing a mathematically sophisticated introduction to functional analytical concepts.</P>
<P>The text is interesting...
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<P>This book considers classical and current theory and practice, of supervised, unsupervised and semisupervised pattern recognition, to build a complete background for professionals and students of engineering. The authors, leading experts in the f...
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Constructing concise and correct proofs is one of the most challenging aspects of learning to work with advanced mathematics. Meeting this challenge is a defining moment for those considering a career in mathematics or related fields. <EM>A Tran...
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<P>Essential for all biology and biomathematics courses, this textbook provides students with a fresh perspective of quantitative techniques in biology in a field where virtually any advance in the life sciences requires a sophisticated mathematical ...
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<P><EM>Advanced Statistics from an Elementary Point of View</EM> is a highly readable text that communicates the content of a course in mathematical statistics without imposing too much rigor. It clearly emphasizes the connection between statistics a...
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Building on the success of the two previous editions, <EM>Introduction to Hilbert Spaces with Applications, Third Edition</EM>, offers an overview of the basic ideas and results of Hilbert space theory and functional analysis. It acquaints students w...
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<STRONG>Applying Contemporary Statistical Techniques</STRONG> explains why traditional statistical methods are often inadequate or outdated when applied to modern problems. Wilcox demonstrates how new and more powerful techniques address these proble...
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The role of probability in computer science has been growing for years and, in lieu of a tailored textbook, many courses have employed a variety of similar, but not entirely applicable, alternatives. To meet the needs of the computer science graduate...
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<P>Since the publication of the first edition of this classic textbook over thirty years ago, tens of thousands of students have used <EM>A Course in Probability Theory</EM>. New in this edition is an introduction to measure theory that expands the m...
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<EM>Probability and Measure Theory, Second Edition,</EM> is a text for a graduatelevel course in probability that includes essential background topics in analysis. It provides extensive coverage of conditional probability and expectation, strong law...
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<EM>Elements of the Theory of Numbers</EM> teaches students how to develop, implement, and test numerical methods for standard mathematical problems. The authors have created a twopronged pedagogical approach that integrates analysis and algebra wit...
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<P>The purpose, level, and style of this new edition conform to the tenets set forth in the original preface. The authors continue with their tack of developing simultaneously theory and applications, intertwined so that they refurbish and elucidate ...
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