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Statistics and Data Visualization in Climate Science with R and Python
A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate data from station observations, remote sensing and simulated results. For example, students can use R or Python code to read and plot the global warming data and the global precipitation data in netCDF, csv, txt, or JSON; and compute and interpret empirical orthogonal functions. The book's computer code and real-world data allow readers to fully utilize the modern computing technology and updated datasets. Online supplementary resources include R code and Python code, data files, figure files, tutorials, slides and sample syllabi.
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Introduction to Numerical Analysis
New edition of a well-known classic in the field; Previous edition sold over 6000 copies worldwide; Fully-worked examples; Many carefully selected problems
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Surface Analysis
Understand the principles and applications of surface analysis Analyzing the composition of a given surface is a crucial aspect of materials science, with significant bearing on the way a material will interact with a particular environment. Surface analysis draws upon a substantial body of research to analyze the outer few nanometres of a material, and has considerable significance in laboratories studying corrosion, adhesion, polymer surface treatment and more. Surface Analysis offers a comprehensive and accessible overview of the characterization and analysis of outer substrate layers. It brings together experts in each analysis area to lay out foundational theory, offer practical applications, and provide examples. Now fully up to date and reflecting the latest research, it is a must-own for any scientist incorporating surface analysis into laboratory work. Readers of the third edition of Surface Analysis readers will also find: Two new chapters on advanced mass spectrometry methodsDetailed coverage of ever-more-important methods of data analysisTools for concretely improving laboratory and research outcomes Surface Analysis is ideal for practitioners and advanced graduate students in materials science, solid state physics, optics, and chemistry.
R 5,221.00
Introductory Stochastic Analysis for Finance and Insurance
Incorporates the many tools needed for modeling and pricing in finance and insurance Introductory Stochastic Analysis for Finance and Insurance introduces readers to the topics needed to master and use basic stochastic analysis techniques for mathematical finance. The author presents the theories of stochastic processes and stochastic calculus and provides the necessary tools for modeling and pricing in finance and insurance. Practical in focus, the book's emphasis is on application, intuition, and computation, rather than theory. Consequently, the text is of interest to graduate students, researchers, and practitioners interested in these areas. While the text is self-contained, an introductory course in probability theory is beneficial to prospective readers. This book evolved from the author's experience as an instructor and has been thoroughly classroom-tested. Following an introduction, the author sets forth the fundamental information and tools needed by researchers and practitioners working in the financial and insurance industries: * Overview of Probability Theory * Discrete-Time stochastic processes * Continuous-time stochastic processes * Stochastic calculus: basic topics The final two chapters, Stochastic Calculus: Advanced Topics and Applications in Insurance, are devoted to more advanced topics. Readers learn the Feynman-Kac formula, the Girsanov's theorem, and complex barrier hitting times distributions. Finally, readers discover how stochastic analysis and principles are applied in practice through two insurance examples: valuation of equity-linked annuities under a stochastic interest rate environment and calculation of reserves for universal life insurance. Throughout the text, figures and tables are used to help simplify complex theory and pro-cesses. An extensive bibliography opens up additional avenues of research to specialized topics. Ideal for upper-level undergraduate and graduate students, this text is recommended for one-semester courses in stochastic finance and calculus. It is also recommended as a study guide for professionals taking Causality Actuarial Society (CAS) and Society of Actuaries (SOA) actuarial examinations.
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Technical Analysis
Master technical analysis, step-by-step! Already the field's most comprehensive, reliable, and objective introduction, this guidebook has been thoroughly updated to reflect the field's latest advances. Selected by the Market Technicians Association as the official companion to its prestigious Chartered Market Technician (CMT) program, Technical Analysis, Third Edition systematically explains the theory of technical analysis, presenting academic evidence both for and against it. Using hundreds of fully updated illustrations and examples, the authors explain the analysis of both markets and individual issues, and present complete investment systems and portfolio management plans. They present authoritative, up-to-date coverage of tested sentiment, momentum indicators, seasonal effects, flow of funds, testing systems, risk mitigation strategies, and many other topics. Offering 30% new coverage, Technical Analysis, Third Edition thoroughly addresses recent advances in pattern recognition, market analysis, systems management, and confidence testing; Kagi, Renko, Kase, Ichimoku, Clouds, and DeMark indicators; innovations in exit stops, portfolio selection, and testing; implications of behavioral bias, and the recent performance of old formulas and methods. For traders, researchers, and serious investors alike, this is the definitive guide to profiting from technical analysis.
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Electrodynamics Tutorials with Python Simulations
This book provides an accessible introduction to intermediate-level electrodynamics with computational approaches to complement a traditional mathematical treatment of the subject. It covers key topics in electrodynamics, such as electromagnetic fields, forces, potentials, and waves as well as Special Theory of Relativity.Through intuition-building examples and visualizations in the Python programming language, it helps readers to develop technical computing skills in numerical and symbolic calculations, modeling and simulations, and visualizations. Python is a highly readable and practical programming language, making this book appropriate for students without extensive programming experience.This book can serve as an electrodynamics textbook for undergraduate physics and engineering students in their second or third years, who are studying intermediate- or advanced-level electrodynamics and who want to learn techniques for scientific computing at the same time. This book will also appeal to computer science students who want to see how their computer programming skills may be applied to science, particularly to physics, without needing too much background physics knowledge.Key features● Major concepts in classical electrodynamics are introduced cohesively through computational and mathematical treatments.● Computational examples in Python programming language guide students on how to simulate and visualize electrodynamic principles and phenomena for themselves.Taejoon Kouh is a Professor of Nano and Electronic Physics at Kookmin University, Republic of Korea. He earned his B.A. in physics from Boston University and Sc.M. and Ph.D. degrees in physics from Brown University. After his study in Providence, RI, he returned to Boston, MA, and worked as a postdoctoral research associate in the Department of Aerospace and Mechanical Engineering at Boston University. He is a full faculty member in the Department of Nano and Electronic Physics at Kookmin University in Seoul, Korea, teaching and supervising undergraduate and graduate students. His current research involves the dynamics of nanoelectromechanical systems and the development of fast and reliable transduction methods and innovative applications based on tiny motion.Minjoon Kouh is a program scientist for a philanthropic initiative. He was a Professor of Physics and Neuroscience at Drew University, USA, where he taught more than 30 distinct types of courses. He holds Ph.D. and B.S. degrees in physics from MIT and an M.A. from UC Berkeley. He completed a postdoctoral research fellowship at the Salk Institute for Biological Studies in La Jolla, CA. His research includes computational modeling of the primate visual cortex, information-theoretic analysis of neural responses, machine learning, and pedagogical innovations in undergraduate science education.
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Stochastic Analysis
In 5 independent sections, this book accounts recent main developments of stochastic analysis: Gross-Stroock Sobolev space over a Gaussian probability space; quasi-sure analysis; anticipate stochastic integrals as divergence operators; principle of transfer from ordinary differential equations to stochastic differential equations; Malliavin calculus and elliptic estimates; stochastic Analysis in infinite dimension.
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Applied Functional Analysis
Applied Functional Analysis, Third Edition provides a solid mathematical foundation for the subject. It motivates students to study functional analysis by providing many contemporary applications and examples drawn from mechanics and science. This well-received textbook starts with a thorough introduction to modern mathematics before continuing with detailed coverage of linear algebra, Lebesque measure and integration theory, plus topology with metric spaces. The final two chapters provides readers with an in-depth look at the theory of Banach and Hilbert spaces before concluding with a brief introduction to Spectral Theory.The Third Edition is more accessible and promotes interest and motivation among students to prepare them for studying the mathematical aspects of numerical analysis and the mathematical theory of finite elements.
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Symmetry Analysis of Differential Equations with Mathematica®
The first book to explicitly use Mathematica so as to allow researchers and students to more easily compute and solve almost any kind of differential equation using Lie's theory. Previously time-consuming and cumbersome calculations are now much more easily and quickly performed using the Mathematica computer algebra software. The material in this book, and on the accompanying CD-ROM, will be of interest to a broad group of scientists, mathematicians and engineers involved in dealing with symmetry analysis of differential equations. Each section of the book starts with a theoretical discussion of the material, then shows the application in connection with Mathematica. The cross-platform CD-ROM contains Mathematica (version 3.0) notebooks which allow users to directly interact with the code presented within the book. In addition, the author's proprietary "MathLie" software is included, so users can readily learn to use this powerful tool in regard to performing algebraic computations.
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Complex Analysis
This unusual and lively textbook offers a clear and intuitive approach to the classical and beautiful theory of complex variables. With very little dependence on advanced concepts from several-variable calculus and topology, the text focuses on the authentic complex-variable ideas and techniques. Accessible to students at their early stages of mathematical study, this full first year course in complex analysis offers new and interesting motivations for classical results and introduces related topics stressing motivation and technique. Numerous illustrations, examples, and now 300 exercises, enrich the text. Students who master this textbook will emerge with an excellent grounding in complex analysis, and a solid understanding of its wide applicability.
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Basic Concepts of Data and Error Analysis
This introductory textbook explains the concepts and methods of data and error analysis needed for laboratory experiment write-ups, especially physics and engineering experiments. The book contains the material needed for beginning students, e.g., first year university students, college students (enrolled on a certificate or diploma course) and even A-level students. Nevertheless, it also covers the required material for higher year university laboratories, including the final year. Only essential concepts and methods needed for the day-to-day performance of experiments and their subsequent analysis and presentation are included and, at the same time, presented as simply as possible. Non-essential detail is avoided. Chapter five is a stand-alone introduction to probability and statistics aimed at providing a theoretical background to the data and error analysis chapters one to four. Computer methods are introduced in Chapter six. The author hopes this book will serve as a constant reference.
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Trends and Challenges in Categorical Data Analysis
This book provides a selection of modern and sophisticated methodologies for the analysis of large and complex univariate and multivariate categorical data. It gives an overview of a substantive and broad collection of topics in the analysis of categorical data, including association, marginal and graphical models, time series and fixed effects models, as well as modern methods of estimation such as regularization, Bayesian estimation and bias reduction methods, along with new simple measures for model interpretability. Methodological innovations and developments are illustrated and explained through real-world applications, together with useful R packages, allowing readers to replicate most of the analyses using the provided code. The applications span a variety of disciplines, including education, psychology, health, economics, and social sciences.
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Analysis 2
Auf eine moderne und didaktische Vorlesungspräsentation abgestimmt, bietet der zweibändige Analysiszyklus von Prof. Blatter eine gut fundierte Einführung in die Differential- und Integralrechnung. Durch seine anschauliche und mit vielen Beispielen aufgelockerte Darstellung wird insbesondere das Bedürfnis nach Anwendungen - auch aus der Physik - erfüllt. Die dritte Auflage wurde vollständig überarbeitet und neu erfaßt. Schwerpunkte von Band 2 sind die ausführlichere Behandlung der Differentialgleichungen und der Vektoranalysis, sowie der Kapitel zur Fourier-Analysis. In allen Fällen wurde auf zahlreiche Beispiele und die Einbeziehung von Anwendungen aus verschiedenen Bereichen besonderer Wert gelegt.
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Analysis of Capture-Recapture Data
An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the mortality and size of the populations. Capture-recapture methods are also used in other areas, including epidemiology and sociology.With an emphasis on ecology, Analysis of Capture-Recapture Data covers many modern developments of capture-recapture and related models and methods and places them in the historical context of research from the past 100 years. The book presents both classical and Bayesian methods.A range of real data sets motivates and illustrates the material and many examples illustrate biometry and applied statistics at work. In particular, the authors demonstrate several of the modeling approaches using one substantial data set from a population of great cormorants. The book also discusses which computer programs to use for implementing the models and contains 130 exercises that extend the main material. The data sets, computer programs, and other ancillaries are available at www.capturerecapture.co.uk.The book is accessible to advanced undergraduate and higher-level students, quantitative ecologists, and statisticians. It helps readers understand model formulation and applications, including the technicalities of model diagnostics and checking.
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AI for Games, Third Edition
AI is an integral part of every video game and this book helps game developers keep up with the constantly evolving technological advances to create robust AI. The authors draw on their considerable experience and uses case studies from real games to provide a complete reference. Also included are exercises so readers can test their comprehension and understanding of the concepts and practices presented.This revised and updated Third Edition includes new techniques, algorithms, data structures and representations needed to create powerful AI in games. It helps experienced game developers learn new techniques and provides students with a solid understanding of game AI that will help them jumpstart their careers.
R 1,903.00
Solutions Manual to accompany An Introduction to Numerical Methods and Analysis
A solutions manual to accompany An Introduction to Numerical Methods and Analysis, Third Edition An Introduction to Numerical Methods and Analysis helps students gain a solid understanding of a wide range of numerical approximation methods for solving problems of mathematical analysis. Designed for entry-level courses on the subject, this popular textbook maximizes teaching flexibility by first covering basic topics before gradually moving to more advanced material in each chapter and section. Throughout the text, students are provided clear and accessible guidance on a wide range of numerical methods and analysis techniques, including root-finding, numerical integration, interpolation, solution of systems of equations, and many others. This fully revised third edition contains new sections on higher-order difference methods, the bisection and inertia method for computing eigenvalues of a symmetric matrix, a completely re-written section on different methods for Poisson equations, and spectral methods for higher-dimensional problems. New problem sets—ranging in difficulty from simple computations to challenging derivations and proofs—are complemented by computer programming exercises, illustrative examples, and sample code. This acclaimed textbook: Explains how to both construct and evaluate approximations for accuracy and performanceCovers both elementary concepts and tools and higher-level methods and solutionsFeatures new and updated material reflecting new trends and applications in the fieldContains an introduction to key concepts, a calculus review, an updated primer on computer arithmetic, a brief history of scientific computing, a survey of computer languages and software, and a revised literature reviewIncludes an appendix of proofs of selected theorems and author-hosted companion website with additional exercises, application models, and supplemental resources
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Case Files Pharmacology, Third Edition
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.REAL-LIFE CLINICAL CASES FOR THE BASIC SCIENCES AND USMLE STEP 1Experience with clinical cases is key to excelling on the USMLE Step 1 and shelf exams, and ultimately to providing patients with competent clinical care. Case Files: Pharmacology provides 56 true-to-life clinicalcases that illustrate essential concepts in pharmacology. Each case includes an easy-to-understand discussion correlated to key basic science concepts, definitions of key terms, pharmacology pearls, and USMLE-style review questions. With Case Files, you'll learn instead of memorize.Learn from 56 high-yield cases, each with board-style questionsMaster key concepts with clinical pearlsPolish your approach to clinical problems and to patient careMaximize your board scores with the proven Case Files system
R 1,779.00
Applied Behavior Analysis, Global Edition
Appropriate for all upper-level courses in basic principles, applications, and behavioural research methods. This text provides an accurate, comprehensive, and contemporary description of applied behavior analysis in order to help students acquire fundamental knowledge and skills. Applied Behavior Analysis provides a comprehensive, in-depth discussion of the field, offering a complete description of the principles and procedures for changing and analysing socially important behaviour. The 3rd Edition features coverage of advances in all three interrelated domains of the sciences of behavior–theoretical, basic research, and applied research. It also includes updated and new content on topics such as negative reinforcement (Ch. 12), motivation (Ch. 16), verbal behavior (Ch. 18), functional behavioural assessment (Ch. 25), and ethics (Ch. 29).
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Biomedical Engineering Fundamentals, Third Edition
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Fully updated fundamental biomedical engineering principles and technologiesThis state-of-the-art resource offers unsurpassed coverage of fundamental concepts that enable advances in the field of biomedical engineering. Biomedical Engineering Fundamentals, Third Edition, contains all the information you need to improve efficacy and efficiency in problem solving, no matter how simple or complex the problem. Thoroughly revised by experts across the biomedical engineering discipline, this hands-on guide provides the foundational knowledge required for the development of innovative devices, techniques, and treatments.Coverage includes:Modeling of biomedical systems and heat transfer applicationsPhysical and flow properties of bloodRespiratory mechanics and gas exchangeRespiratory muscles, human movement, and the musculoskeletal systemElectromyography and muscle forcesBiopolymers, biomedical composites, and bioceramicsCardiovascular, dental, and orthopedic biomaterialsTissue regeneration and regenerative medicineBioelectricity, biomedical signal analysis, and biosensorsNeural engineering and electrical stimulation of nervous systemsCauses of medical device failure and FDA requirementsCardiovascular, respiratory, and artificial kidney devicesInfrared and ultrasound imaging, MRIs, and nuclear medicineImaging, laser Doppler, and fetal and optical monitoringComputer-integrated surgery and medical roboticsIntelligent assistive technology and rehabilitatorsArtificial limbs, hip and knee replacement, and sensory augmentationHealthcare systems engineering and medical informaticsHospital information systems and computer-based patient recordsSterile medical device package development
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Matrix Analysis Of Framed Structures
Intended for structural engineers, this third edition text, a source on the use of matrix analysis for structures of all types, has been revised and updated.
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Introduction to Correspondence Analysis
Master the fundamentals of correspondence analysis with this illuminating resource An Introduction to Correspondence Analysis assists researchers in improving their familiarity with the concepts, terminology, and application of several variants of correspondence analysis. The accomplished academics and authors deliver a comprehensive and insightful treatment of the fundamentals of correspondence analysis, including the statistical and visual aspects of the subject. Written in three parts, the book begins by offering readers a description of two variants of correspondence analysis that can be applied to two-way contingency tables for nominal categories of variables. Part Two shifts the discussion to categories of ordinal variables and demonstrates how the ordered structure of these variables can be incorporated into a correspondence analysis. Part Three describes the analysis of multiple nominal categorical variables, including both multiple correspondence analysis and multi-way correspondence analysis. Readers will benefit from explanations of a wide variety of specific topics, for example: Simple correspondence analysis, including how to reduce multidimensional space, measuring symmetric associations with the Pearson Ratio, constructing low-dimensional displays, and detecting statistically significant pointsNon-symmetrical correspondence analysis, including quantifying asymmetric associationsSimple ordinal correspondence analysis, including how to decompose the Pearson Residual for ordinal variablesMultiple correspondence analysis, including crisp coding and the indicator matrix, the Burt Matrix, and stackingMulti-way correspondence analysis, including symmetric multi-way analysis Perfect for researchers who seek to improve their understanding of key concepts in the graphical analysis of categorical data, An Introduction to Correspondence Analysis will also assist readers already familiar with correspondence analysis who wish to review the theoretical and foundational underpinnings of crucial concepts.
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Performance Analysis and Modeling of Digital Transmission Systems
This book is an expanded third edition of the book Performance Analysis of Digital Transmission Systems, originally published in 1990. Second edition of the book titled Digital Transmission Systems: Performance Analysis and Modeling was published in 1998. The book is intended for those who design communication systems and networks. A computer network designer is interested in selecting communication channels, error protection schemes, and link control protocols. To do this efficiently, one needs a mathematical model that accurately predicts system behavior. Two basic problems arise in mathematical modeling: the problem of identifying a system and the problem of applying a model to the system analysis. System identification consists of selecting a class of mathematical objects to describe fundamental properties of the system behavior. We use a specific class of hidden Markov models (HMMs) to model communication systems. This model was introduced by C. E. Shannon more than 50 years ago as a Noisy Discrete Channel with a finite number of states. The model is described by a finite number of matrices whose elements are estimated on the basis of experimental data. We develop several methods of model identification and show their relationship to other methods of data analysis, such as spectral methods, autoregressive moving average CARMA) approximations, and rational transfer function approximations.
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Real and Convex Analysis
This book offers a first course in analysis for scientists and engineers. It can be used at the advanced undergraduate level or as partof the curriculum in a graduate program. The book is built around metric spaces. In the first three chapters, the authors lay the foundational material and cover the all-important “four-C’s”: convergence, completeness, compactness, and continuity. In subsequent chapters, the basic tools of analysis are used to give briefintroductions to differential and integral equations, convex analysis, and measure theory. The treatment is modern and aesthetically pleasing. It lays the groundwork for the needs of classical fields as well as the important newfields of optimization and probability theory.
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Comparison of the Bayesian and Frequentist Approaches to Estimation
The main theme of this monograph is “comparative statistical inference. ” While the topics covered have been carefully selected (they are, for example, restricted to pr- lems of statistical estimation), my aim is to provide ideas and examples which will assist a statistician, or a statistical practitioner, in comparing the performance one can expect from using either Bayesian or classical (aka, frequentist) solutions in - timation problems. Before investing the hours it will take to read this monograph, one might well want to know what sets it apart from other treatises on comparative inference. The two books that are closest to the present work are the well-known tomes by Barnett (1999) and Cox (2006). These books do indeed consider the c- ceptual and methodological differences between Bayesian and frequentist methods. What is largely absent from them, however, are answers to the question: “which - proach should one use in a given problem?” It is this latter issue that this monograph is intended to investigate. There are many books on Bayesian inference, including, for example, the widely used texts by Carlin and Louis (2008) and Gelman, Carlin, Stern and Rubin (2004). These books differ from the present work in that they begin with the premise that a Bayesian treatment is called for and then provide guidance on how a Bayesian an- ysis should be executed. Similarly, there are many books written from a classical perspective.
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Input-Output Analysis
This essential reference for students and scholars in the input-output research and applications community has been fully revised and updated to reflect important developments in the field. Expanded coverage includes construction and application of multiregional and interregional models, including international models and their application to global economic issues such as climate change and international trade; structural decomposition and path analysis; linkages and key sector identification and hypothetical extraction analysis; the connection of national income and product accounts to input-output accounts; supply and use tables for commodity-by-industry accounting and models; social accounting matrices; non-survey estimation techniques; and energy and environmental applications. Input-Output Analysis is an ideal introduction to the subject for advanced undergraduate and graduate students in many scholarly fields, including economics, regional science, regional economics, city, regional and urban planning, environmental planning, public policy analysis and public management.
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Theory of Sampling and Sampling Practice, Third Edition
A step-by-step guide for anyone challenged by the many subtleties of sampling particulate materials. The only comprehensive document merging the famous works of P. Gy, I. Visman, and C.O. Ingamells into a single theory in a logical way - the most advanced book on sampling that can be used by all sampling practitioners around the world.
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Advanced Machine Learning with Python
Solve challenging data science problems by mastering cutting-edge machine learning techniques in PythonAbout This Book• Resolve complex machine learning problems and explore deep learning• Learn to use Python code for implementing a range of machine learning algorithms and techniques• A practical tutorial that tackles real-world computing problems through a rigorous and effective approachWho This Book Is ForThis title is for Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution, or of entering a Kaggle contest for instance, this book is for you!Prior experience of Python and grounding in some of the core concepts of machine learning would be helpful.What You Will Learn• Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms• Apply your new found skills to solve real problems, through clearly-explained code for every technique and test• Automate large sets of complex data and overcome time-consuming practical challenges• Improve the accuracy of models and your existing input data using powerful feature engineering techniques• Use multiple learning techniques together to improve the consistency of results• Understand the hidden structure of datasets using a range of unsupervised techniques• Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach• Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models togetherIn DetailDesigned to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.By this end of th
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Electromagnetic Simulation Using the FDTD Method with Python
Provides an introduction to the Finite Difference Time Domain method and shows how Python code can be used to implement various simulations This book allows engineering students and practicing engineers to learn the finite-difference time-domain (FDTD) method and properly apply it toward their electromagnetic simulation projects. Each chapter contains a concise explanation of an essential concept and instruction on its implementation into computer code. Included projects increase in complexity, ranging from simulations in free space to propagation in dispersive media. This third edition utilizes the Python programming language, which is becoming the preferred computer language for the engineering and scientific community. Electromagnetic Simulation Using the FDTD Method with Python, Third Edition is written with the goal of enabling readers to learn the FDTD method in a manageable amount of time. Some basic applications of signal processing theory are explained to enhance the effectiveness of FDTD simulation. Topics covered in include one-dimensional simulation with the FDTD method, two-dimensional simulation, and three-dimensional simulation. The book also covers advanced Python features and deep regional hyperthermia treatment planning. Electromagnetic Simulation Using the FDTD Method with Python: Guides the reader from basic programs to complex, three-dimensional programs in a tutorial fashionIncludes a rewritten fifth chapter that illustrates the most interesting applications in FDTD and the advanced graphics techniques of PythonCovers peripheral topics pertinent to time-domain simulation, such as Z-transforms and the discrete Fourier transformProvides Python simulation programs on an accompanying website An ideal book for senior undergraduate engineering students studying FDTD, Electromagnetic Simulation Using the FDTD Method with Python will also benefit scientists and engineers interested in the subject.
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Hands-On Web Scraping with Python
Work through practical examples to unlock the full potential of web scraping with Python and gain valuable insights from high-quality dataKey FeaturesBuild an initial portfolio of web scraping projects with detailed explanationsGrasp Python programming fundamentals related to web scraping and data extractionAcquire skills to code web scrapers, store data in desired formats, and employ the data professionallyPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWeb scraping is a powerful tool for extracting data from the web, but it can be daunting for those without a technical background. Designed for novices, this book will help you grasp the fundamentals of web scraping and Python programming, even if you have no prior experience.Adopting a practical, hands-on approach, this updated edition of Hands-On Web Scraping with Python uses real-world examples and exercises to explain key concepts. Starting with an introduction to web scraping fundamentals and Python programming, you’ll cover a range of scraping techniques, including requests, lxml, pyquery, Scrapy, and Beautiful Soup. You’ll also get to grips with advanced topics such as secure web handling, web APIs, Selenium for web scraping, PDF extraction, regex, data analysis, EDA reports, visualization, and machine learning.This book emphasizes the importance of learning by doing. Each chapter integrates examples that demonstrate practical techniques and related skills. By the end of this book, you’ll be equipped with the skills to extract data from websites, a solid understanding of web scraping and Python programming, and the confidence to use these skills in your projects for analysis, visualization, and information discovery.What you will learnMaster web scraping techniques to extract data from real-world websitesImplement popular web scraping libraries such as requests, lxml, Scrapy, and pyqueryDevelop advanced skills in web scraping, APIs, PDF extraction, regex, and machine learningAnalyze and visualize data with Pandas and PlotlyDevelop a practical portfolio to demonstrate your web scraping skillsUnderstand best practices and ethical concerns in web scraping and data extractionWho this book is forThis book is for beginners who want to learn web scraping and data extraction using Python. No prior programming knowledge is required, but a basic understanding of web-related concepts such as websites, browsers, and HTML is assumed. If you enjoy learning by doing and want to build a portfolio of web scraping projects and delve into data-related studies and application, then this book is tailored for your needs.
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Applied Behavior Analysis
This text provides an accurate, comprehensive, and contemporary description of applied behavior analysis in order to help readers acquire fundamental knowledge and skills Applied Behavior Analysis provides a comprehensive, in-depth discussion of the field, offering a complete description of the principles and procedures for changing and analyzing socially important behavior. The 3rd Edition features coverage of advances in all three interrelated domains of the sciences of behavior–theoretical, basic research, and applied research–and two new chapters, Equivalence-based Instruction (Ch. 19) and Engineering Emergent Learning with Nonequivalence Relations (Ch. 20). It also includes updated and new content on topics such as negative reinforcement (Ch. 12), motivation (Ch. 16), verbal behavior (Ch. 18), functional behavioral assessment (Ch. 27), and ethics (Ch. 31). The content of the text is now connected to the BCBA® and BCABA® Behavior Analyst Task List, 5th Edition.
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Multilevel Analysis
The Second Edition of this classic text introduces the main methods, techniques and issues involved in carrying out multilevel modeling and analysis. Snijders and Bosker′s book is an applied, authoritative and accessible introduction to the topic, providing readers with a clear conceptual and practical understanding of all the main issues involved in designing multilevel studies and conducting multilevel analysis. This book provides step-by-step coverage of: • multilevel theories • ecological fallacies • the hierarchical linear model • testing and model specification • heteroscedasticity • study designs • longitudinal data • multivariate multilevel models • discrete dependent variables There are also new chapters on: • missing data • multilevel modeling and survey weights • Bayesian and MCMC estimation and latent-class models. This book has been comprehensively revised and updated since the last edition, and now discusses modeling using HLM, MLwiN, SAS, Stata including GLLAMM, R, SPSS, Mplus, WinBugs, Latent Gold, and SuperMix. This is a must-have text for any student, teacher or researcher with an interest in conducting or understanding multilevel analysis. Tom A.B. Snijders is Professor of Statistics in the Social Sciences at the University of Oxford and Professor of Statistics and Methodology at the University of Groningen. Roel J. Bosker is Professor of Education and Director of GION, Groningen Institute for Educational Research, at the University of Groningen.
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Meta-Analysis of Controlled Clinical Trials
Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research. This has mainly been due to greater emphasis on evidence-based medicine and the need for reliable summaries of the vast and expanding volume of clinical research. At the same time there have been great strides in the development and refinement of the associated statistical methodology. This book describes the planning, conduct and reporting of a meta-analysis as applied to a series of randomized controlled clinical trials. The various approaches are presented within a general unified framework.Meta-analysis techniques are described in detail, from their theoretical development through to practical implementation.Each topic discussed is supported by detailed worked examples.A comparison of fixed and random effects approaches is included, as well as a discussion of Bayesian methods and cumulative meta-analysis.Fully documented programs using standard statistical procedures in SAS are available on the Web. Ideally suited for practising statisticians and statistically-minded medical professionals, the book will also be of use to graduate students of medical statistics. The book is a self-contained and comprehensive account of the subject and an essential purchase for anyone involved in clinical trials.
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Social Science Data Analysis
In this book, basic statistical knowledge is conveyed in an understandable and application-oriented manner. The readers should be enabled to carry out their own empirical evaluations and to understand or critically reflect on existing analyses.The third edition is extended by a detailed chapter on the logic of significance tests.A replication syntax for the statistical program Stata is provided online as supplementary material.
R 2,729.91
Multiphase Flows with Droplets and Particles, Third Edition
Multiphase Flows with Droplets and Particles provides an organized, pedagogical study of multiphase flows with particles and droplets. This revised edition presents new information on particle interactions, particle collisions, thermophoresis and Brownian movement, computational techniques and codes, and the treatment of irregularly shaped particles. An entire chapter is devoted to the flow of nanoparticles and applications of nanofluids. Features Discusses the modelling and analysis of nanoparticles. Covers all fundamental aspects of particle and droplet flows. Includes heat and mass transfer processes. Features new and updated sections throughout the text. Includes chapter exercises and a Solutions Manual for adopting instructors.Designed to complement a graduate course in multiphase flows, the book can also serve as a supplement in short courses for engineers or as a stand-alone reference for engineers and scientists who work in this area.
R 3,738.72
Applied Longitudinal Data Analysis for Medical Science
Essential for non-statisticians and researchers working with longitudinal data from medical studies, this updated new edition discusses the most important techniques available for analysing data of this type. Using non-technical language, the book explores simple methods such as the paired t-test and summary statistics as well as more sophisticated regression-based methods, including mixed model analysis. The emphasis of the discussion lies in the interpretation of the results of these different methods, covering data analysis with continuous, dichotomous, categorical and other outcome variables. Datasets used throughout the book are provided, enabling readers to re-analyse the examples as they make their way through chapters and improve their understanding of the material. Finally, an extensive and practical overview of, and comparison between, different software packages is provided. Readers will be able to use this book as a practical manual in their everyday work without needing a strong background in statistics.
R 2,491.00
R 1,627.00
Statistical Analysis of Epidemiologic Data
Analytic procedures suitable for the study of human disease are scattered throughout the statistical and epidemiologic literature. Explanations of their properties are frequently presented in mathematical and theoretical language. This well-established text gives readers a clear understanding of the statistical methods that are widely used in epidemiologic research without depending on advanced mathematical or statistical theory. By applying these methods to actualdata, Selvin reveals the strengths and weaknesses of each analytic approach. He combines techniques from the fields of statistics, biostatistics, demography and epidemiology to present a comprehensive overview that does not require computational details of the statistical techniques described.For the Third Edition, Selvin took out some old material (e.g. the section on rarely used cross-over designs) and added new material (e.g. sections on frequently used contingency table analysis). Throughout the text he enriched existing discussions with new elements, including the analysis of multi-level categorical data and simple, intuitive arguments that exponential survival times cause the hazard function to be constant. He added a dozen new applied examples to illustrate such topics as thepitfalls of proportional mortality data, the analysis of matched pair categorical data, and the age-adjustment of mortality rates based on statistical models. The most important new feature is a chapter on Poisson regression analysis. This essential statistical tool permits the multivariableanalysis of rates, probabilities and counts.
R 3,980.63
Practical Bifurcation and Stability Analysis
Probably the first book to describe computational methods for numerically computing steady state and Hopf bifurcations. Requiring only a basic knowledge of calculus, and using detailed examples, problems, and figures, this is an ideal textbook for graduate students.
R 3,070.07
Introduction to Research Methods and Data Analysis in Psychology
This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods. Highly practical in nature, the book guides you, step-by-step, through the research process and is underpinned by SPSS screenshots, diagrams and examples throughout.
R 3,004.00
