This self-contained book addresses the underlying mathematical theory behind the reconstruction and analysis of phylogenies. The theory is grounded in classical concepts from discrete mathematics and probability theory as well as techniques from other branches of mathematics (algebra, topology, differential equations). The biological relevance of the results is highlighted throughout. The author supplies proofs of key classical theorems and includes results not covered in existing books, emphasizes relevant mathematical results derived over the past 20 years, and provides numerous exercises, examples, and figures.
The Essentials For Dummies Series
Dummies is proud to present our new series, The Essentials ForDummies. Now students who are prepping for exams, preparing tostudy new material, or who just need a refresher can have aconcise, easy-to-understand review guide that covers an entirecourse by concentrating solely on the most important concepts. Fromalgebra and chemistry to grammar and Spanish, our expert authorsfocus on the skills students most need to succeed in a subject.
A long life in a healthy, vigorous, youthful body has always been one of humanity's greatest dreams. Recent progress in genetic manipulations and calorie-restricted diets in laboratory animals hold forth the promise that someday science will enable us to exert total control over our own biological aging.
Nearly all scientists who study the biology of aging agree that we will someday be able to substantially slow down the aging process, extending our productive, youthful lives. Dr. Aubrey de Grey is perhaps the most bullish of all such researchers. As has been reported in media outlets ranging from 60 Minutes to The New York Times, Dr. de Grey believes that the key biomedical technology required to eliminate aging-derived debilitation and death entirely—technology that would not only slow but periodically reverse age-related physiological decay, leaving us biologically young into an indefinite future—is now within reach.
In Ending Aging, Dr. de Grey and his research assistant Michael Rae describe the details of this biotechnology. They explain that the aging of the human body, just like the aging of man-made machines, results from an accumulation of various types of damage. As with man-made machines, this damage can periodically be repaired, leading to indefinite extension of the machine's fully functional lifetime, just as is routinely done with classic cars. We already know what types of damage accumulate in the human body, and we are moving rapidly toward the comprehensive development of technologies to remove that damage. By demystifying aging and its postponement for the nonspecialist reader, de Grey and Rae systematically dismantle the fatalist presumption that aging will forever defeat the efforts of medical science.
This highly versatile text provides mathematical background used in a wide variety of disciplines, including mathematics and mathematics education, computer science, biology, chemistry, engineering, communications, and business.
Some of the major features and strengths of this textbook
More than 1,600 exercises, ranging from elementary to challenging, are included with hints/answers to all odd-numbered exercises.
Descriptions of proof techniques are accessible and lively.
Students benefit from the historical discussions throughout the textbook.
Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
This edition includes greatly expanded focus on stem cells, including adult and embryonic stem cells and progenitor populations that may soon lead to new tissue engineering therapies for heart disease, diabetes, and a wide variety of other diseases that afflict humanity. This up-to-date coverage of stem cell biology and other emerging technologies is complemented by a series of new chapters on recent clinical experience in applying tissue engineering. The result is a comprehensive textbook that we believe will be useful to students and experts alike.
New to this edition:
*Includes new chapters on biomaterial-protein interactions, nanocomposite and three-dimensional scaffolds, skin substitutes, spinal cord, vision enhancement, and heart valves
*Expanded coverage of adult and embryonic stem cells of the cardiovascular, hematopoietic, musculoskeletal, nervous, and other organ systems
The Lean Product Playbook is a practical guide to building products that customers love. Whether you work at a startup or a large, established company, we all know that building great products is hard. Most new products fail. This book helps improve your chances of building successful products through clear, step-by-step guidance and advice.
The Lean Startup movement has contributed new and valuable ideas about product development and has generated lots of excitement. However, many companies have yet to successfully adopt Lean thinking. Despite their enthusiasm and familiarity with the high-level concepts, many teams run into challenges trying to adopt Lean because they feel like they lack specific guidance on what exactly they should be doing.
If you are interested in Lean Startup principles and want to apply them to develop winning products, this book is for you. This book describes the Lean Product Process: a repeatable, easy-to-follow methodology for iterating your way to product-market fit. It walks you through how to:Determine your target customersIdentify underserved customer needsCreate a winning product strategyDecide on your Minimum Viable Product (MVP)Design your MVP prototypeTest your MVP with customersIterate rapidly to achieve product-market fit
This book was written by entrepreneur and Lean product expert Dan Olsen whose experience spans product management, UX design, coding, analytics, and marketing across a variety of products. As a hands-on consultant, he refined and applied the advice in this book as he helped many companies improve their product process and build great products. His clients include Facebook, Box, Hightail, Epocrates, and Medallia.
Entrepreneurs, executives, product managers, designers, developers, marketers, analysts and anyone who is passionate about building great products will find The Lean Product Playbook an indispensable, hands-on resource.
The second edition adds a discussion of vector auto-regressive, structural vector auto-regressive, and structural vector error-correction models. To analyze the interactions between the investigated variables, further impulse response function and forecast error variance decompositions are introduced as well as forecasting. The author explains how these model types relate to each other.
One is heuristic and nonrigorous, and attempts to develop in students an intuitive feel for the subject that enables him or her to think probabilistically. The other approach attempts a rigorous development of probability by using the tools of measure theory. The first approach is employed in this text.
The book begins by introducing basic concepts of probability theory, such as the random variable, conditional probability, and conditional expectation. This is followed by discussions of stochastic processes, including Markov chains and Poison processes. The remaining chapters cover queuing, reliability theory, Brownian motion, and simulation. Many examples are worked out throughout the text, along with exercises to be solved by students.
This book will be particularly useful to those interested in learning how probability theory can be applied to the study of phenomena in fields such as engineering, computer science, management science, the physical and social sciences, and operations research. Ideally, this text would be used in a one-year course in probability models, or a one-semester course in introductory probability theory or a course in elementary stochastic processes.
New to this Edition:
65% new chapter material including coverage of finite capacity queues, insurance risk models and Markov chainsContains compulsory material for new Exam 3 of the Society of Actuaries containing several sections in the new examsUpdated data, and a list of commonly used notations and equations, a robust ancillary package, including a ISM, SSM, and test bankIncludes SPSS PASW Modeler and SAS JMP software packages which are widely used in the field
Superior writing styleExcellent exercises and examples covering the wide breadth of coverage of probability topics Real-world applications in engineering, science, business and economics
The author begins with basic characteristics of financial timeseries data before covering three main topics:Analysis and application of univariate financial timeseriesThe return series of multiple assetsBayesian inference in finance methods
Key features of the new edition include additional coverage ofmodern day topics such as arbitrage, pair trading, realizedvolatility, and credit risk modeling; a smooth transition fromS-Plus to R; and expanded empirical financial data sets.
The overall objective of the book is to provide some knowledgeof financial time series, introduce some statistical tools usefulfor analyzing these series and gain experience in financialapplications of various econometric methods.
1,001 Statistics Practice Problems For Dummies takes youbeyond the instruction and guidance offered in Statistics ForDummies to give you a more hands-on understanding of statistics.The practice problems offered range in difficulty, includingdetailed explanations and walk-throughs.
In this series, every step of every solution is shown withexplanations and detailed narratives to help you solve eachproblem. With the book purchase, you’ll also get access topractice statistics problems online. This content features 1,001practice problems presented in multiple choice format; on-the-goaccess from smart phones, computers, and tablets; customizablepractice sets for self-directed study; practice problemscategorized as easy, medium, or hard; and a one-year subscriptionwith book purchase.Offers on-the-go access to practice statistics problemsGives you friendly, hands-on instruction1,001 statistics practice problems that range indifficulty
1,001 Statistics Practice Problems For Dummies providesample practice opportunities for students who may have takenstatistics in high school and want to review the most importantconcepts as they gear up for a faster-paced college class.
". . . [this book] should be on the shelf of everyone interestedin . . . longitudinal data analysis."
—Journal of the American Statistical Association
Features newly developed topics and applications of theanalysis of longitudinal data
Applied Longitudinal Analysis, Second Edition presentsmodern methods for analyzing data from longitudinal studies and nowfeatures the latest state-of-the-art techniques. The bookemphasizes practical, rather than theoretical, aspects of methodsfor the analysis of diverse types of longitudinal data that can beapplied across various fields of study, from the health and medicalsciences to the social and behavioral sciences.
The authors incorporate their extensive academic and researchexperience along with various updates that have been made inresponse to reader feedback. The Second Edition features six newlyadded chapters that explore topics currently evolving in the field,including:Fixed effects and mixed effects modelsMarginal models and generalized estimating equationsApproximate methods for generalized linear mixed effectsmodelsMultiple imputation and inverse probability weightedmethodsSmoothing methods for longitudinal dataSample size and power
Each chapter presents methods in the setting of applications todata sets drawn from the health sciences. New problem sets havebeen added to many chapters, and a related website features sampleprograms and computer output using SAS, Stata, and R, as well asdata sets and supplemental slides to facilitate a completeunderstanding of the material.
With its strong emphasis on multidisciplinary applications andthe interpretation of results, Applied LongitudinalAnalysis, Second Edition is an excellent book for courses onstatistics in the health and medical sciences at theupper-undergraduate and graduate levels. The book also serves as avaluable reference for researchers and professionals in themedical, public health, and pharmaceutical fields as well as thosein social and behavioral sciences who would like to learn moreabout analyzing longitudinal data.
"Seamless R and C++ integration with Rcpp" is simply a wonderful book. For anyone who uses C/C++ and R, it is an indispensable resource. The writing is outstanding. A huge bonus is the section on applications. This section covers the matrix packages Armadillo and Eigen and the GNU Scientific Library as well as RInside which enables you to use R inside C++. These applications are what most of us need to know to really do scientific programming with R and C++. I love this book. -- Robert McCulloch, University of Chicago Booth School of Business
Rcpp is now considered an essential package for anybody doing serious computational research using R. Dirk's book is an excellent companion and takes the reader from a gentle introduction to more advanced applications via numerous examples and efficiency enhancing gems. The book is packed with all you might have ever wanted to know about Rcpp, its cousins (RcppArmadillo, RcppEigen .etc.), modules, package development and sugar. Overall, this book is a must-have on your shelf. -- Sanjog Misra, UCLA Anderson School of Management
The Rcpp package represents a major leap forward for scientific computations with R. With very few lines of C++ code, one has R's data structures readily at hand for further computations in C++. Hence, high-level numerical programming can be made in C++ almost as easily as in R, but often with a substantial speed gain. Dirk is a crucial person in these developments, and his book takes the reader from the first fragile steps on to using the full Rcpp machinery. A very recommended book! -- Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark
"Seamless R and C ++ Integration with Rcpp" provides the first comprehensive introduction to Rcpp. Rcpp has become the most widely-used language extension for R, and is deployed by over one-hundred different CRAN and BioConductor packages. Rcpp permits users to pass scalars, vectors, matrices, list or entire R objects back and forth between R and C++ with ease. This brings the depth of the R analysis framework together with the power, speed, and efficiency of C++.
Dirk Eddelbuettel has been a contributor to CRAN for over a decade and maintains around twenty packages. He is the Debian/Ubuntu maintainer for R and other quantitative software, edits the CRAN Task Views for Finance and High-Performance Computing, is a co-founder of the annual R/Finance conference, and an editor of the Journal of Statistical Software. He holds a Ph.D. in Mathematical Economics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.
Storytelling with Data teaches you the fundamentals of data visualization and how to communicate effectively with data. You'll discover the power of storytelling and the way to make data a pivotal point in your story. The lessons in this illuminative text are grounded in theory, but made accessible through numerous real-world examples—ready for immediate application to your next graph or presentation.
Storytelling is not an inherent skill, especially when it comes to data visualization, and the tools at our disposal don't make it any easier. This book demonstrates how to go beyond conventional tools to reach the root of your data, and how to use your data to create an engaging, informative, compelling story. Specifically, you'll learn how to:Understand the importance of context and audienceDetermine the appropriate type of graph for your situationRecognize and eliminate the clutter clouding your informationDirect your audience's attention to the most important parts of your dataThink like a designer and utilize concepts of design in data visualizationLeverage the power of storytelling to help your message resonate with your audience
Together, the lessons in this book will help you turn your data into high impact visual stories that stick with your audience. Rid your world of ineffective graphs, one exploding 3D pie chart at a time. There is a story in your data—Storytelling with Data will give you the skills and power to tell it!
Eve Herold's Beyond Human examines the medical technologies taking shape at the nexus of computing, microelectronics, engineering, nanotechnology, cellular and gene therapies, and robotics. These technologies will dramatically transform our lives and allow us to live for hundreds of years. Yet, with these blessings come complicated practical and ethical issues, some of which we can predict, but many we cannot.
Beyond Human taps the minds of doctors, scientists, and engineers engaged in developing a host of new technologies while telling the stories of some of the patients courageously testing the radical new treatments about to come into the market.
Beyond Human asks the difficult questions of the scientists and bioethicists who seek to ensure that as our bodies and brains become ever more artificial, we hold onto our humanity. In this new world, will everyone have access to technological miracles, or will we end up living in a world of radical disparities? How will society accommodate life spans that extend into hundreds of years? Will we and our descendants be able to bring about the dream of a future liberated by technology, or will we end up merely serving the machines and devices that keep us healthy, smart, young, and alive?
Covering all the mathematical techniques required to resolve geometric problems and design computer programs for computer graphic applications, each chapter explores a specific mathematical topic prior to moving forward into the more advanced areas of matrix transforms, 3D curves and surface patches. Problem-solving techniques using vector analysis and geometric algebra are also discussed.
All the key areas are covered including: Numbers, Algebra, Trigonometry, Coordinate geometry, Transforms, Vectors, Curves and surfaces, Barycentric coordinates, Analytic geometry.
Plus – and unusually in a student textbook – a chapter on geometric algebra is included.
This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables.
Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include:A chapter on the analysis of correlated outcome dataA wealth of additional material for topics ranging from Bayesian methods to assessing model fitRich data sets from real-world studies that demonstrate each method under discussionDetailed examples and interpretation of the presented results as well as exercises throughout
Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.
Filling the void, Biotechnology Operations: Principles and Practices reflects this integrative philosophy, serving as a practical guide for students, professionals, or anyone else with interests in the biotech industry. Although many books emphasize specific technical aspects of biotech, this is perhaps the first to integrate essential concepts of product development and scientific and management skills with the seven functional areas of biotechnology:
Biomanufacturing Clinical trials Nonclinical studies Project management Quality assurance Quality control Regulatory affairs
A practical roadmap to optimizing biotechnology operations, this reference illustrates how to use specific product planning, design, and project management processes to seamlessly merge plans and efforts in the key functional areas. Applying lessons learned throughout the nascent history of biotech, author Michael Roy highlights developmental principles that could bring future products to market more safely and efficiently. Drawing from his experiences working in industry and teaching a graduate course at the University of Wisconsin, this hotly anticipated book clarifies basic methodologies and practices to help reduce risks and resolve problems as future technological discoveries are developed into tangible products.
“This book should be an essential part of the personallibrary of every practicingstatistician.”—Technometrics
Thoroughly revised and updated, the new edition of NonparametricStatistical Methods includes additional modern topics andprocedures, more practical data sets, and new problems fromreal-life situations. The book continues to emphasize theimportance of nonparametric methods as a significant branch ofmodern statistics and equips readers with the conceptual andtechnical skills necessary to select and apply the appropriateprocedures for any given situation.
Written by leading statisticians, Nonparametric StatisticalMethods, Third Edition provides readers with crucialnonparametric techniques in a variety of settings, emphasizing theassumptions underlying the methods. The book provides an extensivearray of examples that clearly illustrate how to use nonparametricapproaches for handling one- or two-sample location and dispersionproblems, dichotomous data, and one-way and two-way layoutproblems. In addition, the Third Edition features:The use of the freely available R software to aid incomputation and simulation, including many new R programs writtenexplicitly for this new editionNew chapters that address density estimation, wavelets,smoothing, ranked set sampling, and Bayesian nonparametricsProblems that illustrate examples from agricultural science,astronomy, biology, criminology, education, engineering,environmental science, geology, home economics, medicine,oceanography, physics, psychology, sociology, and spacescienceNonparametric Statistical Methods, Third Edition is anexcellent reference for applied statisticians and practitioners whoseek a review of nonparametric methods and their relevantapplications. The book is also an ideal textbook forupper-undergraduate and first-year graduate courses in appliednonparametric statistics.
The R language is recognized as one of the most powerful andflexible statistical software packages, enabling users to applymany statistical techniques that would be impossible without suchsoftware to help implement such large data sets. R has become anessential tool for understanding and carrying out research.
This edition:Features full colour text and extensive graphicsthroughout.Introduces a clear structure with numbered section headings tohelp readers locate information more efficiently.Looks at the evolution of R over the past five years.Features a new chapter on Bayesian Analysis andMeta-Analysis.Presents a fully revised and updated bibliography and referencesection.Is supported by an accompanying website allowing examples fromthe text to be run by the user.
Praise for the first edition:
‘…if you are an R user or wannabe R user, this textis the one that should be on your shelf. The breadth oftopics covered is unsurpassed when it comes to texts on dataanalysis in R.’ (The American Statistician, August2008)‘The High-level software language of R is setting standardsin quantitative analysis. And now anybody can get to grips with itthanks to The R Book…’ (Professional Pensions,July 2007)
This new edition discusses biological systems that can be analyzed quantitatively, and how advances in the life sciences have been aided by the knowledge of physical or engineering analysis techniques. The volume is organized into 18 chapters encompassing thermodynamics, electricity, optics, sound, solid mechanics, fluid mechanics, and atomic and nuclear physics. Each chapter provides a brief review of the background physics before focusing on the applications of physics to biology and medicine. Topics range from the role of diffusion in the functioning of cells to the effect of surface tension on the growth of plants in soil and the conduction of impulses along the nervous system. Each section contains problems that explore and expand some of the concepts. The text includes many figures, examples and illustrative problems and appendices which provide convenient access to the most important concepts of mechanics, electricity, and optics in the body.
Physics in Biology and Medicine will be a valuable resource for students and professors of physics, biology, and medicine, as well as for applied health workers.Provides practical techniques for applying knowledge of physics to the study of living systemsPresents material in a straight forward manner requiring very little background in physics or biologyIncludes many figures, examples and illustrative problems and appendices which provide convenient access to the most important concepts of mechanics, electricity, and optics in the body
"It is, as far as I'm concerned, among the best books in math ever written....if you are a mathematician and want to have the top reference in probability, this is it." (Amazon.com, January 2006)
A complete and comprehensive classic in probability and measure theory
Probability and Measure, Anniversary Edition by Patrick Billingsley celebrates the achievements and advancements that have made this book a classic in its field for the past 35 years. Now re-issued in a new style and format, but with the reliable content that the third edition was revered for, this Anniversary Edition builds on its strong foundation of measure theory and probability with Billingsley's unique writing style. In recognition of 35 years of publication, impacting tens of thousands of readers, this Anniversary Edition has been completely redesigned in a new, open and user-friendly way in order to appeal to university-level students.
This book adds a new foreward by Steve Lally of the Statistics Department at The University of Chicago in order to underscore the many years of successful publication and world-wide popularity and emphasize the educational value of this book. The Anniversary Edition contains features including:An improved treatment of Brownian motionReplacement of queuing theory with ergodic theoryTheory and applications used to illustrate real-life situationsOver 300 problems with corresponding, intensive notes and solutionsUpdated bibliographyAn extensive supplement of additional notes on the problems and chapter commentaries
Patrick Billingsley was a first-class, world-renowned authority in probability and measure theory at a leading U.S. institution of higher education. He continued to be an influential probability theorist until his unfortunate death in 2011. Billingsley earned his Bachelor's Degree in Engineering from the U.S. Naval Academy where he served as an officer. he went on to receive his Master's Degree and doctorate in Mathematics from Princeton University.Among his many professional awards was the Mathematical Association of America's Lester R. Ford Award for mathematical exposition. His achievements through his long and esteemed career have solidified Patrick Billingsley's place as a leading authority in the field and been a large reason for his books being regarded as classics.
This Anniversary Edition of Probability and Measure offers advanced students, scientists, and engineers an integrated introduction to measure theory and probability. Like the previous editions, this Anniversary Edition is a key resource for students of mathematics, statistics, economics, and a wide variety of disciplines that require a solid understanding of probability theory.
Interested in unraveling the physics of living things? Here's your starting point. Biophysics Demystified is the fast and easy way to understand this fascinating topic.
Written in a step-by-step format, this practical guide begins with an introduction to the science of biophysics, covering biophysical techniques and applications. Next, you'll learn the principles of physics, biology, and chemistry required to understand biophysics, including free energy, entropy, and statistical mechanics. Biomolecules and the forces that influence their structure and conformation are also covered, as are protein, nucleic acid, and membrane biophysics. Detailed examples and concise explanations make it easy to understand the material, and end-of-chapter quizzes and a final exam help reinforce key concepts.
It's a no-brainer! You'll get:Molecular, subcellular, physiological, anatomical, and environmental biophysics The laws of thermodynamics as they apply to biophysical systems Forces affecting conformation in biological molecules The composition and structure of carbohydrates, lipids, proteins, and nucleic acids The fluid mosaic model
Simple enough for a beginner, but challenging enough for an advanced student, Biophysics Demystified makes this interdisciplinary subject easy to master.
One of the most diverse of modern scientific disciplines, biophysics applies methods and technologies from physics to the study of biological systems and phenomena, from the human nervous system to soil erosion to global warming. What are the best options for satisfying the world's growing energy demands? How can we feed the world's growing population? How can we contain, or reverse, global warming? How can we vouchsafe a plentiful supply of potable water for future generations? These are among the critical questions to which biophysicists work to provide answers.Biophysics courses are increasingly taken by students of biology, physics, chemistry, biochemistry, physiology, statistics, bioengineering, neuroscience, computer science, pharmacology, agriculture,and many moreProvides a friendly, unintimidating overview of the material covered in a typical college-level biophysics courseA one-stop reference, course supplement and exam preparation tool for university students currently enrolled in an introductory biophysics coursesAn indispensable resource for those studying the natural sciences, biological sciences, and physics, as well as math, statistics,computer science, pharmacology and many other disciplinesThe current job market for people well versed in biophysics is very strong, and biophysics is currently listed as one of the fast-growing occupations in the North America
Machine Learning: Hands-On for Developers and TechnicalProfessionals provides hands-on instruction and fully-codedworking examples for the most common machine learning techniquesused by developers and technical professionals. The book contains abreakdown of each ML variant, explaining how it works and how it isused within certain industries, allowing readers to incorporate thepresented techniques into their own work as they follow along. Acore tenant of machine learning is a strong focus on datapreparation, and a full exploration of the various types oflearning algorithms illustrates how the proper tools can help anydeveloper extract information and insights from existing data. Thebook includes a full complement of Instructor's Materials tofacilitate use in the classroom, making this resource useful forstudents and as a professional reference.
At its core, machine learning is a mathematical, algorithm-basedtechnology that forms the basis of historical data mining andmodern big data science. Scientific analysis of big data requires aworking knowledge of machine learning, which forms predictionsbased on known properties learned from training data. MachineLearning is an accessible, comprehensive guide for thenon-mathematician, providing clear guidance that allows readersto:Learn the languages of machine learning including Hadoop,Mahout, and WekaUnderstand decision trees, Bayesian networks, and artificialneural networksImplement Association Rule, Real Time, and Batch learningDevelop a strategic plan for safe, effective, and efficientmachine learning
By learning to construct a system that can learn from data,readers can increase their utility across industries. Machinelearning sits at the core of deep dive data analysis andvisualization, which is increasingly in demand as companiesdiscover the goldmine hiding in their existing data. For the techprofessional involved in data science, Machine Learning:Hands-On for Developers and Technical Professionals providesthe skills and techniques required to dig deeper.
The handbook begins with a series of historical vignettes of pioneers from the last two centuries. It also presents the fundamentals of physics and biology as applied to photomedicine. It next examines conditions and diseases caused by light, including skin cancer, dermatoses, and immunosuppression.
The remainder of the book focuses on the most important clinical therapeutic applications of different kinds of light that vary in both wavelength and intensity. The book discusses ultraviolet phototherapy for skin diseases and infections and presents the basic science of photodynamic therapy and its use in cancer therapy and other medical specialties. It then covers mechanistic studies and clinical applications of low-level laser (light) therapy as well as the use of high power or surgical laser therapy in specialties, such as dentistry and dermatology. The book concludes with a collection of miscellaneous types of phototherapy.
The Clinical Engineering Handbook meets a long felt need for a comprehensive book on all aspects of clinical engineering that is a suitable reference in hospitals, classrooms, workshops, and governmental and non-governmental organization. The Handbook’s thirteen sections address the following areas: Clinical Engineering; Models of Clinical Engineering Practice; Technology Management; Safety Education and Training; Design, Manufacture, and Evaluation and Control of Medical Devices; Utilization and Service of Medical Devices; Information Technology; and Professionalism and Ethics. The Clinical Engineering Handbook provides the reader with prospects for the future of clinical engineering as well as guidelines and standards for best practice around the world. From telemedicine and IT issues, to sanitation and disaster planning, it brings together all the important aspects of clinical engineering.Clinical Engineers are the safety and quality faciltators in all medical facilitiesThe most definitive, comprehensive, and up-to-date book available on the subject of clinical engineeringOver 170 contributions by leaders in the field of clinical engineering
The extensively revised second edition provides further clarification of matters that typically give rise to difficulty in the classroom and restructures the chapters on logic to emphasize the role of consequence relations and higher-level rules, as well as including more exercises and solutions.
Topics and features: teaches finite mathematics as a language for thinking, as much as knowledge and skills to be acquired; uses an intuitive approach with a focus on examples for all general concepts; brings out the interplay between the qualitative and the quantitative in all areas covered, particularly in the treatment of recursion and induction; balances carefully the abstract and concrete, principles and proofs, specific facts and general perspectives; includes highlight boxes that raise common queries and clear away confusions; provides numerous exercises, with selected solutions, to test and deepen the reader’s understanding.
This clearly-written text/reference is a must-read for first-year undergraduate students of computing. Assuming only minimal mathematical background, it is ideal for both the classroom and independent study.
The Qlik platform was designed to provide a fast and easy data analytics tool, and QlikView Your Business is your detailed, full-color, step-by-step guide to understanding Qlikview's powerful features and techniques so you can quickly start unlocking your data’s potential. This expert author team brings real-world insight together with practical business analytics, so you can approach, explore, and solve business intelligence problems using the robust Qlik toolset and clearly communicate your results to stakeholders using powerful visualization features in QlikView and Qlik Sense.
This book starts at the basic level and dives deep into the most advanced QlikView techniques, delivering tangible value and knowledge to new users and experienced developers alike. As an added benefit, every topic presented in the book is enhanced with tips, tricks, and insightful recommendations that the authors accumulated through years of developing QlikView analytics.
This is the book for you:
The book covers three common business scenarios - Sales, Profitability, and Inventory Analysis. Each scenario contains four chapters, covering the four main disciplines of business analytics: Business Case, Data Modeling, Scripting, and Visualizations.
The material is organized by increasing levels of complexity. Following our comprehensive tutorial, you will learn simple and advanced QlikView and Qlik Sense concepts, including the following:
How to use the Data Load Script language for implementing data modeling techniquesHow to build and use the QVD data layerBuilding a multi-tier data architecturesUsing variables, loops, subroutines, and other script control statementsAdvanced scripting techniques for a variety of ETL solutionsBuilding Insightful Visualizations in QlikView:
Introduction into QlikView sheet objects — List Boxes, Text Objects, Charts, and moreDesigning insightful Dashboards in QlikViewUsing advanced calculation techniques, such as Set Analysis and Advanced AggregationUsing variables for What-If Analysis, as well as using variables for storing calculations, colors, and selection filtersAdvanced visualization techniques - normalized and non-normalized Mekko charts, Waterfall charts, Whale Tail charts, and more
Building Insightful Visualizations in Qlik Sense:
Whether you are just starting out with QlikView or are ready to dive deeper, QlikView Your Business is your comprehensive guide to sharpening your QlikView skills and unleashing the power of QlikView in your organization.
Across various industries, compensation professionals work toorganize and analyze aspects of employment that deal with elementsof pay, such as deciding base salary, bonus, and commissionprovided by an employer to its employees for work performed.Acknowledging the numerous quantitative analyses of data that are apart of this everyday work, Statistics for Compensation provides acomprehensive guide to the key statistical tools and techniquesneeded to perform those analyses and to help organizations makefully informed compensation decisions.
This self-contained book is the first of its kind to explore theuse of various quantitative methods—from basic notions aboutpercents to multiple linear regression—that are used in themanagement, design, and implementation of powerful compensationstrategies. Drawing upon his extensive experience as a consultant,practitioner, and teacher of both statistics and compensation, theauthor focuses on the usefulness of the techniques and theirimmediate application to everyday compensation work, thoroughlyexplaining major areas such as:
Frequency distributions and histograms
Measures of location and variability
Exponential curve models
Maturity curve models
Market models and salary survey analysis
Linear and exponential integrated market models
Job pricing market models
Throughout the book, rigorous definitions and step-by-stepprocedures clearly explain and demonstrate how to apply thepresented statistical techniques. Each chapter concludes with a setof exercises, and various case studies showcase the topic'sreal-world relevance. The book also features an extensive glossaryof key statistical terms and an appendix with technical details.Data for the examples and practice problems are available in thebook and on a related FTP site.
Statistics for Compensation is an excellent reference forcompensation professionals, human resources professionals, andother practitioners responsible for any aspect of base pay,incentive pay, sales compensation, and executive compensation intheir organizations. It can also serve as a supplement forcompensation courses at the upper-undergraduate and graduatelevels.
"This book is . . . an excellent source of examples forregression analysis. It has been and still is readily readable andunderstandable."
—Journal of the American StatisticalAssociation Regression analysis is a conceptually simplemethod for investigating relationships among variables. Carryingout a successful application of regression analysis, however,requires a balance of theoretical results, empirical rules, andsubjective judgment. Regression Analysis by Example, FifthEdition has been expanded and thoroughly updated to reflectrecent advances in the field. The emphasis continues to be onexploratory data analysis rather than statistical theory. The bookoffers in-depth treatment of regression diagnostics,transformation, multicollinearity, logistic regression, and robustregression.
The book now includes a new chapter on the detection andcorrection of multicollinearity, while also showcasing the use ofthe discussed methods on newly added data sets from the fields ofengineering, medicine, and business. The Fifth Edition alsoexplores additional topics, including:Surrogate ridge regressionFitting nonlinear modelsErrors in variablesANOVA for designed experiments
Methods of regression analysis are clearly demonstrated, andexamples containing the types of irregularities commonlyencountered in the real world are provided. Each example isolatesone or two techniques and features detailed discussions, therequired assumptions, and the evaluated success of each technique.Additionally, methods described throughout the book can be carriedout with most of the currently available statistical softwarepackages, such as the software package R.
Regression Analysis by Example, Fifth Edition is suitablefor anyone with an understanding of elementary statistics.
The book begins by tracing the development of cryptology from that of an arcane practice used, for example, to conceal alchemic recipes, to the modern scientific method that is studied and employed today. The remainder of the book explores the modern aspects and applications of cryptography, covering symmetric- and public-key cryptography, cryptographic protocols, key management, message authentication, e-mail and Internet security, and advanced applications such as wireless security, smart cards, biometrics, and quantum cryptography. The author also includes non-cryptographic security issues and a chapter devoted to information theory and coding. Nearly 200 diagrams, examples, figures, and tables along with abundant references and exercises complement the discussion.
Written by leading authority and best-selling author on the subject Richard A. Mollin, Codes: The Guide to Secrecy from Ancient to Modern Times is the essential reference for anyone interested in this exciting and fascinating field, from novice to veteran practitioner.
Avoiding the hype of popular science and the pessimism of most social science, Nikolas Rose analyzes contemporary molecular biopolitics, examining developments in genomics, neuroscience, pharmacology, and psychopharmacology and the ways they have affected racial politics, crime control, and psychiatry. Rose analyzes the transformation of biomedicine from the practice of healing to the government of life; the new emphasis on treating disease susceptibilities rather than disease; the shift in our understanding of the patient; the emergence of new forms of medical activism; the rise of biocapital; and the mutations in biopower. He concludes that these developments have profound consequences for who we think we are, and who we want to be.
It covers the topics traditionally treated in a first course, but also highlights new and emerging themes. Chapters are broken down into `lecture' sized pieces, motivated and illustrated by numerous theoretical and computational examples.
Over 200 exercises are provided and these are starred according to their degree of difficulty. Solutions to all exercises are available to authorized instructors.
The book covers key foundation topics:
o Taylor series methods
o Runge--Kutta methods
o Linear multistep methods
and a range of modern themes:
o Adaptive stepsize selection
o Long term dynamics
o Modified equations
o Geometric integration
o Stochastic differential equations
The prerequisite of a basic university-level calculus class is assumed, although appropriate background results are also summarized in appendices. A dedicated website for the book containing extra information can be found via www.springer.com
This book is aimed at business analysts with basic programming skills for using R for Business Analytics. Note the scope of the book is neither statistical theory nor graduate level research for statistics, but rather it is for business analytics practitioners. Business analytics (BA) refers to the field of exploration and investigation of data generated by businesses. Business Intelligence (BI) is the seamless dissemination of information through the organization, which primarily involves business metrics both past and current for the use of decision support in businesses. Data Mining (DM) is the process of discovering new patterns from large data using algorithms and statistical methods. To differentiate between the three, BI is mostly current reports, BA is models to predict and strategize and DM matches patterns in big data. The R statistical software is the fastest growing analytics platform in the world, and is established in both academia and corporations for robustness, reliability and accuracy.
The book utilizes Albert Einstein’s famous remarks on making things as simple as possible, but no simpler. This book will blow the last remaining doubts in your mind about using R in your business environment. Even non-technical users will enjoy the easy-to-use examples. The interviews with creators and corporate users of R make the book very readable. The author firmly believes Isaac Asimov was a better writer in spreading science than any textbook or journal author.
Wouldn't it be wonderful if studying statistics were easier?With U Can: Statistics I For Dummies, it is! This one-stopresource combines lessons, practical examples, study questions, andonline practice problems to provide you with the ultimate guide tohelp you score higher in your statistics course. Foundationalstatistics skills are a must for students of many disciplines, andleveraging study materials such as this one to supplement yourstatistics course can be a life-saver. Because U Can: StatisticsI For Dummies contains both the lessons you need to learn andthe practice problems you need to put the concepts into action,you'll breeze through your scheduled study time.
Statistics is all about collecting and interpreting data, and isapplicable in a wide range of subject areas—which translatesinto its popularity among students studying in diverse programs.So, if you feel a bit unsure in class, rest assured that there isan easy way to help you grasp the nuances of statistics!Understand statistical ideas, techniques, formulas, andcalculationsInterpret and critique graphs and charts, determineprobability, and work with confidence intervalsCritique and analyze data from polls and experimentsCombine learning and applying your new knowledge with practicalexamples, practice problems, and expanded online resources
U Can: Statistics I For Dummies contains everything youneed to score higher in your fundamental statistics course!
This concise introductory paperback surveys and relates basic physics to living systems. It discusses biological systems that can be analyzed quantitatively, and how advances in the life sciences have been aided by the knowledge of physical or engineering analysis techniques.
This text is designed for premed students, doctors, nurses, physiologists, or other applied health workers, and other individuals who wish to understand the nature of the mechanics of our bodies.- Provides practical techniques for applying knowledge of physics to the study of living systems
- Presents material in a straight forward manner requiring very little background in physics or biology
- Includes many figures, examples and illustrative problems and appendices which provide convenient access to the most important concepts of mechanics, electricity, and optics
The ever-growing use of derivative products makes it essentialfor financial industry practitioners to have a solid understandingof derivative pricing. To cope with the growing complexity,narrowing margins, and shortening life-cycle of the individualderivative product, an efficient, yet modular, implementation ofthe pricing algorithms is necessary. Mathematical Finance isthe first book to harmonize the theory, modeling, andimplementation of today's most prevalent pricing models under oneconvenient cover. Building a bridge from academia to practice, thisself-contained text applies theoretical concepts to real-worldexamples and introduces state-of-the-art, object-orientedprogramming techniques that equip the reader with the conceptualand illustrative tools needed to understand and develop successfulderivative pricing models.
Utilizing almost twenty years of academic and industryexperience, the author discusses the mathematical concepts that arethe foundation of commonly used derivative pricing models, andinsightful Motivation and Interpretation sections for each conceptare presented to further illustrate the relationship between theoryand practice. In-depth coverage of the common characteristics foundamongst successful pricing models are provided in addition to keytechniques and tips for the construction of these models. Theopportunity to interactively explore the book's principal ideas andmethodologies is made possible via a related Web site that featuresinteractive Java experiments and exercises.
While a high standard of mathematical precision is retained,Mathematical Finance emphasizes practical motivations,interpretations, and results and is an excellent textbook forstudents in mathematical finance, computational finance, andderivative pricing courses at the upper undergraduate or beginninggraduate level. It also serves as a valuable reference forprofessionals in the banking, insurance, and asset managementindustries.
This book can be used as a text for a year long graduate course in statistics, computer science, or mathematics, for self-study, and as an invaluable research reference on probabiliity and its applications. Particularly worth mentioning are the treatments of distribution theory, asymptotics, simulation and Markov Chain Monte Carlo, Markov chains and martingales, Gaussian processes, VC theory, probability metrics, large deviations, bootstrap, the EM algorithm, confidence intervals, maximum likelihood and Bayes estimates, exponential families, kernels, and Hilbert spaces, and a self contained complete review of univariate probability.
“The book follows faithfully the style of the original edition. The approach is heavily motivated by real-world time series, and by developing a complete approach to model building, estimation, forecasting and control."
- Mathematical Reviews
Bridging classical models and modern topics, the Fifth Edition of Time Series Analysis: Forecasting and Control maintains a balanced presentation of the tools for modeling and analyzing time series. Also describing the latest developments that have occurred in the field over the past decade through applications from areas such as business, finance, and engineering, the Fifth Edition continues to serve as one of the most influential and prominent works on the subject.
Time Series Analysis: Forecasting and Control, Fifth Edition provides a clearly written exploration of the key methods for building, classifying, testing, and analyzing stochastic models for time series and describes their use in five important areas of application: forecasting; determining the transfer function of a system; modeling the effects of intervention events; developing multivariate dynamic models; and designing simple control schemes. Along with these classical uses, the new edition covers modern topics with new features that include:A redesigned chapter on multivariate time series analysis with an expanded treatment of Vector Autoregressive, or VAR models, along with a discussion of the analytical tools needed for modeling vector time seriesAn expanded chapter on special topics covering unit root testing, time-varying volatility models such as ARCH and GARCH, nonlinear time series models, and long memory modelsNumerous examples drawn from finance, economics, engineering, and other related fieldsThe use of the publicly available R software for graphical illustrations and numerical calculations along with scripts that demonstrate the use of R for model building and forecastingUpdates to literature references throughout and new end-of-chapter exercisesStreamlined chapter introductions and revisions that update and enhance the expositionTime Series Analysis: Forecasting and Control, Fifth Edition is a valuable real-world reference for researchers and practitioners in time series analysis, econometrics, finance, and related fields. The book is also an excellent textbook for beginning graduate-level courses in advanced statistics, mathematics, economics, finance, engineering, and physics.
Written by a highly-experienced author, Foundations of Linear and Generalized Linear Models is a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding.
The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models, Foundations ofLinear and Generalized Linear Models also features:An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methodsAn overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problemsNumerous examples that use R software for all text data analysesMore than 400 exercises for readers to practice and extend the theory, methods, and data analysisA supplementary website with datasets for the examples and exercisesAn invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses, Foundations of Linear and Generalized Linear Models is also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data.
This concise and easy-to-read textbook/reference presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations.
Topics and features: thoroughly describes the essential concepts of analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives and antiderivatives, definite integrals and double integrals, and curves; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text, together with a list of relevant textbooks and references for further reading; supplementary software can be downloaded from the book’s webpage at www.springer.com.
This textbook is essential for undergraduate students in Computer Science. Written to specifically address the needs of computer scientists and researchers, it will also serve professionals looking to bolster their knowledge in such fundamentals extremely well.
Addressing the highly competitive and risky environments ofcurrent-day financial and sports gambling markets, Forecasting inFinancial and Sports Gambling Markets details the dynamic processof constructing effective forecasting rules based on both graphicalpatterns and adaptive drift modeling (ADM) of cointegrated timeseries. The book uniquely identifies periods of inefficiency thatthese markets oscillate through and develops profitable forecastingmodels that capitalize on irrational behavior exhibited duringthese periods.
Providing valuable insights based on the author's firsthandexperience, this book utilizes simple, yet unique, candlestickcharts to identify optimal time periods in financial markets andoptimal games in sports gambling markets for which forecastingmodels are likely to provide profitable trading and wageringoutcomes. Featuring detailed examples that utilize actual data, thebook addresses various topics that promote financial andmathematical literacy, including:
Higher order ARMA processes in financial markets
The effects of gambling shocks in sports gambling markets
Cointegrated time series with model drift
Throughout the book, interesting real-world applications arepresented, and numerous graphical procedures illustrate favorabletrading and betting opportunities, which are accompanied bymathematical developments in adaptive model forecasting and riskassessment. A related web site features updated reviews in sportsand financial forecasting and various links on the topic.
Forecasting in Financial and Sports Gambling Markets is anexcellent book for courses on financial economics and time seriesanalysis at the upper-undergraduate and graduate levels. The bookis also a valuable reference for researchers and practitionersworking in the areas of retail markets, quant funds, hedge funds,and time series. Also, anyone with a general interest in learningabout how to profit from the financial and sports gambling marketswill find this book to be a valuable resource.