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Understanding Atmospheric Rivers Using Machine Learning (SpringerBriefs in Applied Sciences and Technology)
by Manish Kumar Goyal Shivam SinghThis book delves into the characterization, impacts, drivers, and predictability of atmospheric rivers (AR). It begins with the historical background and mechanisms governing AR formation, giving insights into the global and regional perspectives of ARs, observing their varying manifestations across different geographical contexts. The book explores the key characteristics of ARs, from their frequency and duration to intensity, unraveling the intricate relationship between atmospheric rivers and precipitation. The book also focus on the intersection of ARs with large-scale climate oscillations, such as El Niño and La Niña events, the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). The chapters help understand how these climate phenomena influence AR behavior, offering a nuanced perspective on climate modeling and prediction. The book also covers artificial intelligence (AI) applications, from pattern recognition to prediction modeling and early warning systems. A case study on AR prediction using deep learning models exemplifies the practical applications of AI in this domain. The book culminates by underscoring the interdisciplinary nature of AR research and the synergy between atmospheric science, climatology, and artificial intelligence
Understanding Audiences, Customers, and Users via Analytics: An Introduction to the Employment of Web, Social, and Other Types of Digital People Data (Synthesis Lectures on Information Concepts, Retrieval, and Services)
by Bernard J. Jansen Kholoud K. Aldous Joni Salminen Hind Almerekhi Soon-gyo JungThis book presents the foundations of using analytics from the laboratory, social media platforms, and the web. The authors cover key topics including analytics strategy, data gathering approaches, data preprocessing, data quality assessment, analytical methods, tools, and validation methods. The book includes chapters explaining web analytics, social media analytics, and how to create an analytics strategy. The authors also cover on data sources, such as online surveys, crowdsourcing, eye tracking, mouse tracking, social media APIs, search logs, and analytics triangulation. The book also discusses analytical tools for social media analytics, search analytics, persona analytics, user studies, and website analytics. The authors conclude by examining the validity of online analytics.
Understanding Basic Statistics
by Charles Henry Brase Corrinne Pellillo BraseNIMAC-sourced textbook
Understanding Basic Statistics
by Charles Henry Brase Corrinne Pellillo BraseNIMAC-sourced textbook
Understanding Basic Statistics
by Charles Henry Brase Corrinne Pellillo BraseUNDERSTANDING BASIC STATISTICS provides plenty of guidance and informal advice as it demonstrates the links between statistics and the real world. Its reader-friendly approach helps you grasp the concepts and see how they relate to your life. A complete technology package, including JMP statistical software, gives you the tools you need to practice what you're learning and succeed in the course.
Understanding Basic Statistics
by Charles Henry Brase Corrinne Pellillo BraseNIMAC-sourced textbook
Understanding Basic Statistics
by Charles Henry Brase Corrinne Pellillo BraseA condensed and more streamlined version of the very popular and widely used UNDERSTANDABLE STATISTICS, Ninth Edition, this book offers instructors an effective way to teach the essentials of statistics, including early coverage of Regression, within a more limited time frame. Designed to help students overcome their apprehension about statistics, UNDERSTANDING BASIC STATISTICS, Fifth Edition, is a thorough yet approachable text that provides plenty of guidance and informal advice demonstrating the links between statistics and the world. The strengths of the text include an applied approach that helps students realize the real-world significance of statistics, an accessible exposition, and a new, complete technology package. The Fifth Edition addresses the growing importance of developing students' critical thinking and statistical literacy skills with the introduction of new features and exercises throughout the text. The use of the graphing calculator, Microsoft Excel, Minitab, and SPSS is covered but not required.
Understanding Basic Statistics (Fourth Edition)
by Charles Henry Brase Corrinne Pellillo BraseWelcome to the exciting world of statistics! We have written this text to make statistics accessible to everyone, including those with a limited mathematics background. Statistics affects all aspects of our lives. Whether we are testing new medical devices or determining what will entertain us, applications of statistics are so numerous that, in a sense, we are limited only by our own imagination in discovering new uses for statistics.
Understanding Basic Statistics Sixth Edition
by Charles Henry Brase Corrinne Pellillo BraseUNDERSTANDING BASIC STATISTICS, Sixth Edition, provides plenty of guidance and informal advice demonstrating the links between statistics and the real world. Thorough yet abbreviated, the text offers a reader-friendly style and a new, complete technology package to supplement learning.
Understanding Biostatistics
by Anders KällénUnderstanding Biostatistics looks at the fundamentals of biostatistics, using elementary statistics to explore the nature of statistical tests.This book is intended to complement first-year statistics and biostatistics textbooks. The main focus here is on ideas, rather than on methodological details. Basic concepts are illustrated with representations from history, followed by technical discussions on what different statistical methods really mean. Graphics are used extensively throughout the book in order to introduce mathematical formulae in an accessible way.Key features:Discusses confidence intervals and p-values in terms of confidence functions. Explains basic statistical methodology represented in terms of graphics rather than mathematical formulae, whilst highlighting the mathematical basis of biostatistics. Looks at problems of estimating parameters in statistical models and looks at the similarities between different models. Provides an extensive discussion on the position of statistics within the medical scientific process. Discusses distribution functions, including the Guassian distribution and its importance in biostatistics. This book will be useful for biostatisticians with little mathematical background as well as those who want to understand the connections in biostatistics and mathematical issues.
Understanding Biplots
by Sugnet Gardner Lubbe Niel J. Le Roux John C. GowerBiplots are a graphical method for simultaneously displaying two kinds of information; typically, the variables and sample units described by a multivariate data matrix or the items labelling the rows and columns of a two-way table. This book aims to popularize what is now seen to be a useful and reliable method for the visualization of multidimensional data associated with, for example, principal component analysis, canonical variate analysis, multidimensional scaling, multiplicative interaction and various types of correspondence analysis.Understanding Biplots:* Introduces theory and techniques which can be applied to problems from a variety of areas, including ecology, biostatistics, finance, demography and other social sciences.* Provides novel techniques for the visualization of multidimensional data and includes data mining techniques.* Uses applications from many fields including finance, biostatistics, ecology, demography.* Looks at dealing with large data sets as well as smaller ones.* Includes colour images, illustrating the graphical capabilities of the methods.* Is supported by a Website featuring R code and datasets.Researchers, practitioners and postgraduate students of statistics and the applied sciences will find this book a useful introduction to the possibilities of presenting data in informative ways.
Understanding Business Dynamics: AN INTEGRATED DATA SYSTEM FOR AMERICA'S FUTURE
by National Research Council of the National AcademiesThe U.S. economy is highly dynamic: businesses open and close, workers switch jobs and start new enterprises, and innovative technologies redefine the workplace and enhance productivity. With globalization markets have also become more interconnected. Measuring business activity in this rapidly evolving environment increasingly requires tracking complex interactions among firms, establishments, employers, and employees. Understanding Business Dynamics presents strategies for improving the accuracy, timeliness, coverage, and integration of data that are used in constructing aggregate economic statistics, as well as in microlevel analyses of topics ranging from job creation and destruction and firm entry and exit to innovation and productivity. This book offers recommendations that could be enacted by federal statistical agencies to modernize the measurement of business dynamics, particularly the production of information on small and young firms that can have a disproportionately large impact in rapidly expanding economic sectors. It also outlines the need for effective coordination of existing survey and administrative data sources, which is essential to improving the depth and coverage of business data.
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.