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A Primer on Linear Models (Chapman And Hall/crc Texts In Statistical Science Ser.)
by John F. MonahanA Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods.
Environmental and Ecological Statistics with R (Chapman And Hall/crc Applied Environmental Statistics Ser.)
by Song S. QianEmphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R connects applied statistics to the environmental and ecological fields. It follows the general approach to solving a statistical modeling problem, covering model specification, parameter estimation, and model evaluation. The author uses many exa
Elements of Compiler Design
by Alexander MedunaMaintaining a balance between a theoretical and practical approach to this important subject, Elements of Compiler Design serves as an introduction to compiler writing for undergraduate students. From a theoretical viewpoint, it introduces rudimental models, such as automata and grammars, that underlie compilation and its essential phases. Based on
Introduction to Abstract Algebra (Textbooks In Mathematics Ser.)
by Jonathan D. SmithTaking a slightly different approach from similar texts, Introduction to Abstract Algebra presents abstract algebra as the main tool underlying discrete mathematics and the digital world. It helps students fully understand groups, rings, semigroups, and monoids by rigorously building concepts from first principles. A Quick Introduction
Introduction to Probability with R (Chapman And Hall/crc Texts In Statistical Science Ser.)
by Kenneth BaclawskiBased on a popular course taught by the late Gian-Carlo Rota of MIT, with many new topics covered as well, Introduction to Probability with R presents R programs and animations to provide an intuitive yet rigorous understanding of how to model natural phenomena from a probabilistic point of view. Although the R programs are small in length, they ar
Java Programming Fundamentals: Problem Solving Through Object Oriented Analysis and Design
by Premchand S. NairWhile Java texts are plentiful, it's difficult to find one that takes a real-world approach, and encourages novice programmers to build on their Java skills through practical exercise. Written by an expert with 19 experience teaching computer programming, Java Programming Fundamentals presents object-oriented programming by employing examples taken
Applied Statistical Inference with MINITAB
by Sally A. LesikThrough clear, step-by-step mathematical calculations, Applied Statistical Inference with MINITAB enables students to gain a solid understanding of how to apply statistical techniques using a statistical software program. It focuses on the concepts of confidence intervals, hypothesis testing, validating model assumptions, and power analysis.Illustr
Fundamental Number Theory with Applications (Discrete Mathematics And Its Applications Ser.)
by Richard A. MollinAn update of the most accessible introductory number theory text available, Fundamental Number Theory with Applications, Second Edition presents a mathematically rigorous yet easy-to-follow treatment of the fundamentals and applications of the subject. The substantial amount of reorganizing makes this edition clearer and more elementary in i
Machine Learning: An Algorithmic Perspective
by Stephen MarslandTraditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but
Environmental Chemometrics: Principles and Modern Applications (Analytical Chemistry Ser.)
by Grady HanrahanMultivariate, heterogeneous data has been traditionally analyzed using the "one at a time" variable approach, often missing the main objective of discovering the relationships among multiple variables and samples. Enter chemometrics, with its powerful tools for design, analysis, and data interpretation of complex environmental systems. Delineating
Grid Computing: Techniques and Applications (Chapman And Hall/crc Computational Science Ser.)
by Barry WilkinsonDesigned for senior undergraduate and first-year graduate students, Grid Computing: Techniques and Applications shows professors how to teach this subject in a practical way. Extensively classroom-tested, it covers job submission and scheduling, Grid security, Grid computing services and software tools, graphical user interfaces, workflow editors,
Introduction to Mathematical Proofs: A Transition (Textbooks In Mathematics Ser.)
by Charles RobertsShows How to Read & Write Mathematical ProofsIdeal Foundation for More Advanced Mathematics CoursesIntroduction to Mathematical Proofs: A Transition facilitates a smooth transition from courses designed to develop computational skills and problem solving abilities to courses that emphasize theorem proving. It helps students develop the skills n
Algorithms in Bioinformatics: A Practical Introduction (Chapman And Hall/crc Mathematical And Computational Biology Ser.)
by Wing-Kin SungThoroughly Describes Biological Applications, Computational Problems, and Various Algorithmic Solutions Developed from the author's own teaching material, Algorithms in Bioinformatics: A Practical Introduction provides an in-depth introduction to the algorithmic techniques applied in bioinformatics. For each topic, the author clearly details the bi
Introduction to Concurrency in Programming Languages (Chapman And Hall/crc Computational Science Ser.)
by Matthew J. SottileExploring how concurrent programming can be assisted by language-level techniques, Introduction to Concurrency in Programming Languages presents high-level language techniques for dealing with concurrency in a general context. It provides an understanding of programming languages that offer concurrency features as part of the language definition.Th
Statistics in Human Genetics and Molecular Biology (Chapman And Hall/crc Texts In Statistical Science Ser.)
by Cavan ReillyFocusing on the roles of different segments of DNA, Statistics in Human Genetics and Molecular Biology provides a basic understanding of problems arising in the analysis of genetics and genomics. It presents statistical applications in genetic mapping, DNA/protein sequence alignment, and analyses of gene expression data from microarray experiments.
Mathematical and Experimental Modeling of Physical and Biological Processes (Textbooks In Mathematics Ser.)
by H. T. BanksThrough several case study problems from industrial and scientific research laboratory applications, Mathematical and Experimental Modeling of Physical and Biological Processes provides students with a fundamental understanding of how mathematics is applied to problems in science and engineering. For each case study problem, the authors discuss why
Statistical Physics of Biomolecules: An Introduction
by Daniel M. ZuckermanFrom the hydrophobic effect to protein-ligand binding, statistical physics is relevant in almost all areas of molecular biophysics and biochemistry, making it essential for modern students of molecular behavior. But traditional presentations of this material are often difficult to penetrate. Statistical Physics of Biomolecules: An Introduction brin
Logistic Regression Models (Chapman And Hall/crc Texts In Statistical Science Ser.)
by Joseph M. HilbeLogistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models t
Introduction to Statistical Limit Theory (Chapman And Hall/crc Texts In Statistical Science Ser.)
by Alan M. PolanskyHelping students develop a good understanding of asymptotic theory, Introduction to Statistical Limit Theory provides a thorough yet accessible treatment of common modes of convergence and their related tools used in statistics. It also discusses how the results can be applied to several common areas in the field.The author explains as much of the
Motivic Integration (Progress In Mathematics Ser. #325)
by Julien Sebag Johannes Nicaise Antoine Chambert-LoirThis monograph focuses on the geometric theory of motivic integration, which takes its values in the Grothendieck ring of varieties. This theory is rooted in a groundbreaking idea of Kontsevich and was further developed by Denef & Loeser and Sebag. It is presented in the context of formal schemes over a discrete valuation ring, without any restriction on the residue characteristic. The text first discusses the main features of the Grothendieck ring of varieties, arc schemes, and Greenberg schemes. It then moves on to motivic integration and its applications to birational geometry and non-Archimedean geometry. Also included in the work is a prologue on p-adic analytic manifolds, which served as a model for motivic integration. With its extensive discussion of preliminaries and applications, this book is an ideal resource for graduate students of algebraic geometry and researchers of motivic integration. It will also serve as a motivation for more recent and sophisticated theories that have been developed since.
Concepts in Quantum Mechanics (Pure And Applied Physics Ser.)
by Vishnu S. MathurTaking a conceptual approach to the subject, Concepts in Quantum Mechanics provides complete coverage of both basic and advanced topics. Following in the footsteps of Dirac's classic work Principles of Quantum Mechanics, it explains all themes from first principles.The authors present alternative ways of representing the state of a physical system,
Introduction to Probability with Mathematica (Textbooks In Mathematics Ser.)
by Kevin J. HastingsUpdated to conform to Mathematica 7.0, Introduction to Probability with Mathematica, Second Edition continues to show students how to easily create simulations from templates and solve problems using Mathematica. It provides a real understanding of probabilistic modeling and the analysis of data and encourages the application of these ideas to prac
Attraction in Numerical Minimization: Iteration Mappings, Attractors, and Basins of Attraction (SpringerBriefs in Optimization)
by Adam B. LevyNumerical minimization of an objective function is analyzed in this book to understand solution algorithms for optimization problems. Multiset-mappings are introduced to engineer numerical minimization as a repeated application of an iteration mapping. Ideas from numerical variational analysis are extended to define and explore notions of continuity and differentiability of multiset-mappings, and prove a fixed-point theorem for iteration mappings. Concepts from dynamical systems are utilized to develop notions of basin size and basin entropy. Simulations to estimate basins of attraction, to measure and classify basin size, and to compute basin are included to shed new light on convergence behavior in numerical minimization. Graduate students, researchers, and practitioners in optimization and mathematics who work theoretically to develop solution algorithms will find this book a useful resource.
Advanced Mathematical Methods in Science and Engineering
by S. I. HayekClassroom-tested, Advanced Mathematical Methods in Science and Engineering, Second Edition presents methods of applied mathematics that are particularly suited to address physical problems in science and engineering. Numerous examples illustrate the various methods of solution and answers to the end-of-chapter problems are included at the back of t
Interdisciplinary Design of Game-based Learning Platforms: A Phenomenological Examination of the Integrative Design of Game, Learning, and Assessment (Advances in Game-Based Learning)
by Fengfeng Ke Valerie Shute Kathleen M. Clark Gordon ErlebacherThis book represents a four-year research and development project. It presents a phenomenological examination and explanation of a functional design framework for games in education. It furnishes a rich description of the experiences and perceptions of performing interdisciplinary collaborative design among experts of very diverse fields, such as learning systems design, architectural design, assessment design, mathematics education, and scientific computing.