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Understanding Clinical Data Analysis
by Ton J. Cleophas Aeilko H. ZwindermanThis textbook consists of ten chapters, and is a must-read to all medical and health professionals, who already have basic knowledge of how to analyze their clinical data, but still, wonder, after having done so, why procedures were performed the way they were. The book is also a must-read to those who tend to submerge in the flood of novel statistical methodologies, as communicated in current clinical reports, and scientific meetings. In the past few years, the HOW-SO of current statistical tests has been made much more simple than it was in the past, thanks to the abundance of statistical software programs of an excellent quality. However, the WHY-SO may have been somewhat under-emphasized. For example, why do statistical tests constantly use unfamiliar terms, like probability distributions, hypothesis testing, randomness, normality, scientific rigor, and why are Gaussian curves so hard, and do they make non-mathematicians getting lost all the time? The book will cover the WHY-SOs.
Understanding Clinical Papers
by David Bowers Allan House David Owens Bridgette BewickUnderstanding Clinical Papers is a popular and well established introduction to reading clinical papers. It unravels the process of evidence-based practice, using real papers to illustrate how to understand and evaluate published research, and it goes on to provide explanations of important research-related topics.
Understanding Complex Biological Systems with Mathematics (Association for Women in Mathematics Series #14)
by Ami Radunskaya Rebecca Segal Blerta ShtyllaThis volume examines a variety of biological and medical problems using mathematical models to understand complex system dynamics. Featured topics include autism spectrum disorder, ectoparasites and allogrooming, argasid ticks dynamics, super-fast nematocyst firing, cancer-immune population dynamics, and the spread of disease through populations. Applications are investigated with mathematical models using a variety of techniques in ordinary and partial differential equations, difference equations, Markov-chain models, Monte-Carlo simulations, network theory, image analysis, and immersed boundary method. Each article offers a thorough explanation of the methodologies used and numerous tables and color illustrations to explain key results. This volume is suitable for graduate students and researchers interested in current applications of mathematical models in the biosciences.The research featured in this volume began among newly-formed collaborative groups at the 2017 Women Advancing Mathematical Biology Workshop that took place at the Mathematical Biosciences Institute in Columbus, Ohio. The groups spent one intensive week working at MBI and continued their collaborations after the workshop, resulting in the work presented in this volume.
Understanding Computational Bayesian Statistics (Wiley Series in Computational Statistics #644)
by William M. BolstadA hands-on introduction to computational statistics from a Bayesian point of view Providing a solid grounding in statistics while uniquely covering the topics from a Bayesian perspective, Understanding Computational Bayesian Statistics successfully guides readers through this new, cutting-edge approach. With its hands-on treatment of the topic, the book shows how samples can be drawn from the posterior distribution when the formula giving its shape is all that is known, and how Bayesian inferences can be based on these samples from the posterior. These ideas are illustrated on common statistical models, including the multiple linear regression model, the hierarchical mean model, the logistic regression model, and the proportional hazards model. The book begins with an outline of the similarities and differences between Bayesian and the likelihood approaches to statistics. Subsequent chapters present key techniques for using computer software to draw Monte Carlo samples from the incompletely known posterior distribution and performing the Bayesian inference calculated from these samples. Topics of coverage include: Direct ways to draw a random sample from the posterior by reshaping a random sample drawn from an easily sampled starting distribution The distributions from the one-dimensional exponential family Markov chains and their long-run behavior The Metropolis-Hastings algorithm Gibbs sampling algorithm and methods for speeding up convergence Markov chain Monte Carlo sampling Using numerous graphs and diagrams, the author emphasizes a step-by-step approach to computational Bayesian statistics. At each step, important aspects of application are detailed, such as how to choose a prior for logistic regression model, the Poisson regression model, and the proportional hazards model. A related Web site houses R functions and Minitab macros for Bayesian analysis and Monte Carlo simulations, and detailed appendices in the book guide readers through the use of these software packages. Understanding Computational Bayesian Statistics is an excellent book for courses on computational statistics at the upper-level undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners who use computer programs to conduct statistical analyses of data and solve problems in their everyday work.
Understanding Correlation Matrices (Quantitative Applications in the Social Sciences)
by Alexandria R. Hadd Joseph Lee RodgersCorrelation matrices (along with their unstandardized counterparts, covariance matrices) underlie the majority the statistical methods that researchers use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one correlation in the matrix puts constraints on the values of the others, and the multivariate implications of this statement is a major theme of the volume. Alexandria Hadd and Joseph Lee Rodgers cover many features of correlations matrices including statistical hypothesis tests, their role in factor analysis and structural equation modeling, and graphical approaches. They illustrate the discussion with a wide range of lively examples including correlations between intelligence measured at different ages through adolescence; correlations between country characteristics such as public health expenditures, health life expectancy, and adult mortality; correlations between well-being and state-level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course. This volume may be used effectively across a number of disciplines in both undergraduate and graduate statistics classrooms, and also in the research laboratory.
Understanding Correlation Matrices (Quantitative Applications in the Social Sciences)
by Alexandria R. Hadd Joseph Lee RodgersCorrelation matrices (along with their unstandardized counterparts, covariance matrices) underlie the majority the statistical methods that researchers use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one correlation in the matrix puts constraints on the values of the others, and the multivariate implications of this statement is a major theme of the volume. Alexandria Hadd and Joseph Lee Rodgers cover many features of correlations matrices including statistical hypothesis tests, their role in factor analysis and structural equation modeling, and graphical approaches. They illustrate the discussion with a wide range of lively examples including correlations between intelligence measured at different ages through adolescence; correlations between country characteristics such as public health expenditures, health life expectancy, and adult mortality; correlations between well-being and state-level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course. This volume may be used effectively across a number of disciplines in both undergraduate and graduate statistics classrooms, and also in the research laboratory.
Understanding Demographic Transitions
by Claude Diebolt Faustine PerrinThis book studies the process of demographic transition which has played a key role in the economic development of Western countries. The special focus is on France, which constitutes the first clear case of fertility decline in Europe. The book analyzes the reasons behind this phenomenon by examining the evolution of demographic variables in France over the past two hundred years. To better understand the reasons of the changing patterns of demographic behavior, the authors investigate the development of the female labor force, study educational investments, and explore the evolution of gender roles and relations.
Understanding Digital Signal Processing with MATLAB and Solutions (The Electrical Engineering and Applied Signal Processing Series)
by Alexander D. PoularikasThe book discusses receiving signals that most electrical engineers detect and study. The vast majority of signals could never be detected due to random additive signals, known as noise, that distorts them or completely overshadows them. Such examples include an audio signal of the pilot communicating with the ground over the engine noise or a bioengineer listening for a fetus’ heartbeat over the mother’s. The text presents the methods for extracting the desired signals from the noise. Each new development includes examples and exercises that use MATLAB to provide the answer in graphic forms for the reader's comprehension and understanding.
Understanding Dyscalculia and Numeracy Difficulties: A Guide for Parents, Teachers and Other Professionals
by Patricia Babtie Jane EmersonDyscalculia is a specific learning difficulty that affects the acquisition of numerical skills. A far larger number of pupils, while not dyscalculic, fail to acquire the basic numerical skills required for everyday life. Whatever the cause of poor numeracy it is essential that these difficulties are identified and addressed. This book looks at how adults can help identify each child's specific areas of difficulty and describes a multi-sensory approach that can be adapted for the needs of each student to help them better understand numbers and apply that understanding to solve problems. It covers the origins of number sense and how the brain deals with numbers, assessment, planning intervention, what to teach and how to teach it, and how parents can help their children. This straightforward guide will be essential reading for any parent, teacher or education professional working with a child with dyscalculia or numeracy difficulties.
Understanding Educational Statistics Using Microsoft Excel® and Spss®
by Martin Lee AbbottUtilizing the latest software, this book presents the essential statistical procedures for drawing valuable results from data in the social sciences. Mobilizing interesting real-world examples from the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS supplies a seamless presentation that identifies valuable connections between statistical applications and research design. Class-tested to ensure an accessible presentation, the book combines clear, step-by-step explanations and the use of software packages that are accessible to both the novice and professional alike to present the fundamental statistical practices for organizing, understanding, and drawing conclusions from educational research data. The book begines with an introduction to descriptive and inferential statistics and then proceeds to acquaint readers with the various functions for working with quantitative data in the Microsoft Excel environment, such as spreadsheet navigation; sorting and filtering; and creating pivot tables. Subsequent chapters treat the procedures that are commonly-employed when working with data across various fields of social science research, including: Single-sample tests Repeated measure tests Independent t-tests One way ANOVA and factorial ANOVA Correlation Bivariate regression Chi square Multiple regression Individual chapters are devoted to specific procedures, each ending with a lab exercise that highlights the importance of that procedure by posing a research question, examining the question through its application in Excel and SPSS, and concluding with a brief research report that outlines key findings drawn from the results. Real-world examples and data from modern educational research are used throughout the book, and a related Web site features additional data sets, examples, and labs, allowing readers to reinforce their comprehension of the material. Bridging traditional statistical topics with the latest software and applications in the field of education, Understanding Educational Statistics Using Microsoft Excel and SPSS is an excellent book for courses on educational research methods and introductory statistics in the social sciences at the upper-undergraduate and graduate levels. It also serves as a valuable resource for researchers and practitioners in the fields of education, psychology, and the social sciences who require a statistical background to work with data in their everyday work.
Understanding Elections through Statistics: Polling, Prediction, and Testing (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
by Ole J. ForsbergElections are random events.From individuals deciding whether to vote, to individuals deciding who to vote for, to election authorities deciding what to count, the outcomes of competitive democratic elections are rarely known until election day… or beyond. Understanding Elections through Statistics explores this random phenomenon from three primary points of view: predicting the election outcome using opinion polls, testing the election outcome using government-reported data, and exploring election data to better understand the people.Written for those with only a brief introduction to statistics, this book takes you on a statistical journey from how polls are taken to how they can—and should—be used to estimate current popular opinion. Once an understanding of the election process is built, we turn toward testing elections for evidence of unfairness. While holding elections has become the de facto proof of government legitimacy, those electoral processes may hide the dirty little secret of the government, illicitly ensuring a favorable election outcome.This book includes these features designed to make your statistical journey more enjoyable: Vignettes of elections, including maps, starting each chapter to motivate the material In-chapter cues to help one avoid the heavy math—or to focus on it End-of-chapter problems designed to review and extend what was covered in the chapter Many opportunities to turn the power of the R Statistical Environment to the enclosed election data files, as well as to those you find interesting The second edition improves upon this and includes: A rewrite of several chapters to make the underlying concepts more clear A chapter dedicated to confidence intervals, what they mean, and what they do not Additional experiments to help you better understand the statistics of elections A new introduction to polling, its terms, its processes, and its ethics From these features, it is clear that the audience for this book is quite diverse. It provides the statistics and mathematics for those interested in statistics and mathematics, but it also provides detours for those who just want a good read and a deeper understanding of elections.
Understanding Family Change and Variation
by Hans-Peter Kohler Pamela Smock Christine A. Bachrach Lynette Hoelter S. Philip Morgan Rosalind King Jennifer A. Johnson-HanksFertility rates vary considerably across and within societies, and over time. Over the last three decades, social demographers have made remarkable progress in documenting these axes of variation, but theoretical models to explain family change and variation have lagged behind. At the same time, our sister disciplines--from cultural anthropology to social psychology to cognitive science and beyond--have made dramatic strides in understanding how social action works, and how bodies, brains, cultural contexts, and structural conditions are coordinated in that process. Understanding Family Change and Variation: Toward a Theory of Conjunctural Action argues that social demography must be reintegrated into the core of theory and research about the processes and mechanisms of social action, and proposes a framework through which that reintegration can occur. This framework posits that material and schematic structures profoundly shape the occurrence, frequency, and context of the vital events that constitute the object of social demography. Fertility and family behaviors are best understood as a function not just of individual traits, but of the structured contexts in which behavior occurs. This approach upends many assumptions in social demography, encouraging demographers to embrace the endogeneity of social life and to move beyond fruitless debates of structure versus culture, of agency versus structure, or of biology versus society.
Understanding General Deterrence
by Stephen L. QuackenbushThis book bridges the divide between formal and quantitative studies of deterrence by empirically testing and extending perfect deterrence theory. The author focuses on general deterrence, which relates to managing relations between states at all times, not only during crises.
Understanding Generative AI Business Applications: A Guide to Technical Principles and Real-World Applications
by Irena CroninThis guide covers the fundamental technical principles and various business applications of Generative AI for planning, developing, and evaluating AI-driven products. It equips you with the knowledge you need to harness the potential of Generative AI for enhancing business creativity and productivity.The book is organized into three sections: text-based, senses-based, and rationale-based. Each section provides an in-depth exploration of the specific methods and applications of Generative AI. In the text-based section, you will find detailed discussions on designing algorithms to automate and enhance written communication, including insights into the technical aspects of transformer-based Natural Language Processing (NLP) and chatbot architecture, such as GPT-4, Claude 2, Google Bard, and others. The senses-based section offers a glimpse into the algorithms and data structures that underpin visual, auditory, and multisensory experiences, including NeRF, 3D Gaussian Splatting,Stable Diffusion, AR and VR technologies, and more. The rationale-based section illuminates the decision-making capabilities of AI, with a focus on machine learning and data analytics techniques that empower applications such as simulation models, agents, and autonomous systems.In summary, this book serves as a guide for those seeking to navigate the dynamic landscape of Generative AI. Whether you’re a seasoned AI professional or a business leader looking to harness the power of creative automation, these pages offer a roadmap to leverage Generative AI for your organization’s success.What You Will LearnWhat are the technical elements that constitute the makeup of Generative AI products?What are the practical applications of Generative AI?How can algorithms be designed to automate and improve written communication?What are the latest Generative AI architectures and algorithms?Who This Book Is ForData scientists, data analysts, decision makers, and business executives interested in gaining an understanding of Generative AI products
Understanding Geographies of Polarization and Peripheralization: Perspectives from Central and Eastern Europe and Beyond (New Geographies of Europe)
by Thilo Lang Sebastian Henn Wladimir Sgibnev Kornelia EhrlichThis book presents a multifaceted perspective on regional development and corresponding processes of adaptation and response, focusing on the concepts of polarization and peripheralization. It discusses theoretical and empirical foundations and presents several compelling case studies from Central and Eastern Europe and beyond.
Understanding Geometric Algebra: Hamilton, Grassmann, and Clifford for Computer Vision and Graphics
by null Kenichi KanataniUnderstanding Geometric Algebra: Hamilton, Grassmann, and Clifford for Computer Vision and Graphics introduces geometric algebra with an emphasis on the background mathematics of Hamilton, Grassmann, and Clifford. It shows how to describe and compute geometry for 3D modeling applications in computer graphics and computer vision.Unlike similar texts
Understanding German Real Estate Markets
by Wolfgang Maennig Tobias JustReal estate is the biggest real asset class in an economy, and Germany is the biggest economy in Europe. This implies opportunities as well as specific risks for investors and policy makers. As the German real estate markets have by and large been spared severe disruptions in the course of the economic crisis, many questions arise for investors and academics alike. What are the key institutional characteristics of the German real estate markets that make it different? What are the short and long-term drivers of demand and supply? Which regional and functional market segments are most likely to outperform in the next few years? What are the most important pitfalls for investors in Germany? This book gives answers to these and many more questions. The editors have invited a broad range of extensively knowledgeable practitioners and academics from across the relevant real estate spectrum, i.e. economic, legal, tax, planning and financing issues, to express their views. There is no better English publication that gives such a profound and simultaneously entertaining overview of Germany's real estate markets.
Understanding German Real Estate Markets (Management for Professionals)
by Tobias Just and Wolfgang MaennigReal estate is the biggest real asset class in an economy, and Germany is the biggest economy in Europe. This implies opportunities as well as specific risks for investors and policy makers. As the German real estate markets have by and large been spared severe disruptions in the course of the economic crisis, many questions arise for investors and academics alike. What are the key institutional characteristics of the German real estate markets that make it different? What are the short and long-term drivers of demand and supply? Which regional and functional market segments are most likely to outperform in the next few years? What are the most important pitfalls for investors in Germany? This book gives answers to these and many more questions. The editors have invited a broad range of extensively knowledgeable practitioners and academics from across the relevant real estate spectrum, i.e. economic, legal, tax, planning and financing issues, to express their views. There is no better English publication that gives such a profound and simultaneously entertaining overview of Germany’s real estate markets.
Understanding Human Life: A Methodological and Interdisciplinary Approach (Methodos Series #19)
by Daniel CourgeauThis book addresses the challenge of understanding human life. It compares our life experience with the attempts to grasp it by astrologers, eugenicists, psychologists, neuroscientists, social scientists, and philosophers. The main opposition among these specialties lies between understanding and misunderstanding. The book also addresses the central methodological difficulty of capturing a human life. It is first examined how certain approaches may lead to a misunderstanding of human life. The book contrasts the example of astrology—an accepted practice in ancient civilizations, but now classified among the pseudosciences—with astronomy, a full-fledged science since Galileo’s time. Another, more recent approach regards human life as predetermined by genes: the methods used by eugenicists, and later by political regimes under the name of hereditarianism, came to compete with genetics. A broader analysis shows how astrology and eugenicism are not truly scientific approaches. Next, the book looks at the ways of capturing an imaginary or real human life story. A comprehensive approach will try to fully understand their complexity, while a more explanatory approach considers only certain specific phenomena of human life. For example, demography studies only births, deaths, and migration. Another crucial factor in the collection of life histories is memory and its transmission. Psychology and psychoanalysis have developed different schools to try to explain them. The book concludes with a detailed discussion of the concepts and tools that have been proposed in more recent times for understanding the various aspects of life stories: mechanisms, systems, hermeneutics, and autonomy.
Understanding Inferential Statistics: From A for Significance Test to Z for Confidence Interval
by Markus Janczyk Roland PfisterWhat does this p-value actually mean? And what is a significant result? This book provides a compact and comprehension-oriented introduction to inferential statistics and answers questions like these. One focus is on the logic underlying inferential statistics and hypothesis testing: Readers learn the most commonly used procedures (t-test, analysis of variance with and without repeated measures, correlation/regression) as well as the pitfalls of data analysis, and develop the understanding necessary to interpret results correctly. The individual chapters are supplemented by concrete evaluation examples from everyday research - including exemplary implementation with the programs SPSS and R. In addition to the classic methods, cross-references to current developments in psychological methodological research are also included.This book is a translation of the original German 3rd edition of Inferenzstatistik verstehen by Markus Janczyk and Roland Pfister. The translation was done with the help of artificial intelligence (machine translation by the service DeepL.com). A subsequent human revision was done primarily in terms of content, so that the book will read stylistically differently from a conventional translation.
Understanding Information Retrieval Systems: Management, Types, and Standards
by Marcia J. BatesIn order to be effective for their users, information retrieval (IR) systems should be adapted to the specific needs of particular environments. The huge and growing array of types of information retrieval systems in use today is on display in Understanding Information Retrieval Systems: Management, Types, and Standards, which addresses over 20 typ
Understanding Institutions: The Science and Philosophy of Living Together
by Francesco GualaUnderstanding Institutions proposes a new unified theory of social institutions that combines the best insights of philosophers and social scientists who have written on this topic. Francesco Guala presents a theory that combines the features of three influential views of institutions: as equilibria of strategic games, as regulative rules, and as constitutive rules.Guala explains key institutions like money, private property, and marriage, and develops a much-needed unification of equilibrium- and rules-based approaches. Although he uses game theory concepts, the theory is presented in a simple, clear style that is accessible to a wide audience of scholars working in different fields. Outlining and discussing various implications of the unified theory, Guala addresses venerable issues such as reflexivity, realism, Verstehen, and fallibilism in the social sciences. He also critically analyses the theory of "looping effects" and "interactive kinds" defended by Ian Hacking, and asks whether it is possible to draw a demarcation between social and natural science using the criteria of causal and ontological dependence. Focusing on current debates about the definition of marriage, Guala shows how these abstract philosophical issues have important practical and political consequences. Moving beyond specific cases to general models and principles, Understanding Institutions offers new perspectives on what institutions are, how they work, and what they can do for us.
Understanding Large Temporal Networks and Spatial Networks
by Vladimir Batagelj Natasa Kejzar Anuska Ferligoj Patrick DoreianThis book explores social mechanisms that drive network change and link them to computationally sound models of changing structure to detect patterns. This text identifies the social processes generating these networks and how networks have evolved.
Understanding Least Squares Estimation and Geomatics Data Analysis
by John Olusegun OgundareProvides a modern approach to least squares estimation and data analysis for undergraduate land surveying and geomatics programs Rich in theory and concepts, this comprehensive book on least square estimation and data analysis provides examples that are designed to help students extend their knowledge to solving more practical problems. The sample problems are accompanied by suggested solutions, and are challenging, yet easy enough to manually work through using simple computing devices, and chapter objectives provide an overview of the material contained in each section. Understanding Least Squares Estimation and Geomatics Data Analysis begins with an explanation of survey observables, observations, and their stochastic properties. It reviews matrix structure and construction and explains the needs for adjustment. Next, it discusses analysis and error propagation of survey observations, including the application of heuristic rule for covariance propagation. Then, the important elements of statistical distributions commonly used in geomatics are discussed. Main topics of the book include: concepts of datum definitions; the formulation and linearization of parametric, conditional and general model equations involving typical geomatics observables; geomatics problems; least squares adjustments of parametric, conditional and general models; confidence region estimation; problems of network design and pre-analysis; three-dimensional geodetic network adjustment; nuisance parameter elimination and the sequential least squares adjustment; post-adjustment data analysis and reliability; the problems of datum; mathematical filtering and prediction; an introduction to least squares collocation and the kriging methods; and more. Contains ample concepts/theory and content, as well as practical and workable examples Based on the author's manual, which he developed as a complete and comprehensive book for his Adjustment of Surveying Measurements and Special Topics in Adjustments courses Provides geomatics undergraduates and geomatics professionals with required foundational knowledge An excellent companion to Precision Surveying: The Principles and Geomatics Practice Understanding Least Squares Estimation and Geomatics Data Analysis is recommended for undergraduates studying geomatics, and will benefit many readers from a variety of geomatics backgrounds, including practicing surveyors/engineers who are interested in least squares estimation and data analysis, geomatics researchers, and software developers for geomatics.
Understanding Machine Learning
by Shai Shalev-Shwartz Shai Ben-DavidMachine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.